Konwolucyjne sieci neuronowe¶

Dziś spróbujemy stworzyć i wytrenować prostą sieć konwolucyjną do rozpoznawania, co znajduje się na obrazie. Następnie omówimy kwestię identyfikowania obiektów na obrazie, oraz porozmawiamy o wykorzystaniu gotowej już sieci.

Problem klasyfikacji obrazów¶

Jak się za to zabrać? Naiwnym podejściem byłaby próba ręcznej specyfikacji pewnych cech (niemowlęta mają duże głowy, szczoteczki są długie, etc.). Szybko jednak stwierdziliśmy, że nawet dla niewielkiego zbioru kategorii jest to tytaniczna praca bez gwarancji sukcesu. Co więcej, istnieje wiele czynników zniekształcających zawartość naszych zdjęć. Obiekty mogą być przedstawiane z różnych ujęć, w różnych warunkach oświetleniowych, w różnej skali, częściowo niewidoczne, ukryte w tle...

obraz.png

Wszystkie wymienione problemy są skutkiem istnienia semantycznej przepaści między tym, jak reprezentowane są nasze dane wejściowe (tablica liczb), a tym, czego w nich szukamy, czyli kategorii i cech: zwierząt, nosów, głów, itp. Zamiast więc próbować samodzielnie napisać funkcję $f(x)$, spróbujemy skorzystać z dobrodziejstw uczenia maszynowego, aby automatycznie skonstruować reprezentację wejścia właściwą dla postawionego sobie zadania (a przynajmniej lepszą od pierwotnej). I tu z pomocą przychodzą nam konwolucyjne sieci neuronowe. Do tego trzeba zrozumieć, czym jest konwolucja (inaczej: splot), a do tego najlepiej nadają się ilustracje, jak to działa.

Konwolucja¶

Konwolucja (splot) to działanie określone dla dwóch funkcji, dające w wyniku inną, która może być postrzegana jako zmodyfikowana wersja oryginalnych funkcji.

Z naszego punktu widzenia polega to na tym, że mnożymy odpowiadające sobie elementy z dwóch macierzy: obrazu, oraz mniejszej, nazywanej filtrem (lub kernelem. Następnie sumujemy wynik i zapisujemy do macierzy wynikowej na odpowiedniej pozycji. Proces powtarza się aż do momentu przeskanowania całego obrazu. Taki filtr wykrywa, czy coś do niego pasuje w danym miejscu, i z tego wynika zdolność semantycznej generalizacji sieci - uczymy się cech, a wykrywamy je potem w dowolnym miejscu. Przydatne pojęcia

1 Zx-ZMLKab7VOCQTxdZ1OAw.gif

Stride¶

Stride to inaczej krok algorytmu, albo przesunięcie. Określa co ile komórek macierzy następuje aplikacja operatora konwolucji. Jeśli stride wynosi 1 a operator konwolucji ma rozmiar np. 3 x 3, to każdy piksel (z wyjątkiem skrajnych narożnych pikseli) będzie uczestniczył w wielu operacjach konwolucji. Jeśli natomiast krok wyniósłby 3, to każdy piksel uczestniczyłby tylko jednokrotnie w tych operacjach. Należy pamiętać, że krok stosujemy zarówno w poziomie, jak i pionie. Najczęściej w obu kierunkach wykorzystuje się ten sam krok.

1 BMngs93_rm2_BpJFH2mS0Q.gif

Padding¶

Padding to inaczej wypełnienie krawędzi obrazu. Określa, w jaki sposób będą traktowane skrajne piksele. Jeśli padding wynosi 0, to skrajne piksele będą uczestniczyły w operacjach konwolucji rzadziej, niż pozostałe piksele (oczywiście jest to również uzależnione od wartości kroku). Aby zniwelować ten efekt, możemy dodać wypełnienie wokół całego obrazu. Te dodatkowe piksele mogą być zerami, albo mogą być również jakimiś uśrednionymi wartościami pikseli sąsiednich. Wypełnienie zerami oznacza de facto obramowanie całego obrazu czarną ramkną.

Więcej na temat wypełnienia.

1 1okwhewf5KCtIPaFib4XaA.gif

Pooling¶

Pooling jest procesem wykorzystywanym do redukcji rozmiaru obrazu. Występują 2 warianty: max-pooling oraz avg-pooling. Pozwala on usunąć zbędne dane, np. jeżeli filtr wykrywa linie, to istnieje spora szansa, że linie te ciągną się przez sąsiednie piksele, więc nie ma powodu powielać tej informacji. Dzięki temu wprowadzamy pewną inwariancję w wagach sieci i jesteśmy odporni na niewielkie wahania lokalizacji informacji, a skupiamy się na "większym obrazie".

11.gif

Sposoby redukcji przeuczenia¶

  • warstwa dropout - wyłączanie losowych neuronów w trakcie uczenia,
  • regularyzacja wag - ograniczenie sumy wartości wag,
  • metoda wczesnego stopu (early stopping) - zatrzymanie uczenia, jeśli proces uczenia nie poprawia wyników,
  • normalizacja paczki (batch normalization) - centrowanie i skalowanie wartości wektorów w obrębie batcha danych,
  • rozszerzanie danych (data augmentation) - generowanie lekko zaburzonych danych, na podstawie danych treningowych,
  • lub... więcej danych.

Budowa sieci CNN do klasyfikacji obrazów¶

Sieć konwolucyjna składa się zawsze najpierw, zgodnie z nazwą, z części konwolucyjnej, której zadaniem jest wyodrębnienie przydatnych cech z obrazu za pomocą filtrów, warstw poolingowych etc.

Warstwa konwolucyjna sieci neuronowej składa się z wielu filtrów konwolucyjnych działających równolegle (tj. wykrywających różne cechy). Wagi kerneli, początkowo zainicjalizowane losowo, są dostrajane w procesie uczenia. Wynik działania poszczególnych filtrów jest przepuszczany przez funkcję nieliniową. Mamy tu do czynienia z sytuacją analogiczną jak w MLP: najpierw wykonujemy przekształcenie liniowe, a potem stosujemy funkcję aktywacji. Funkcji aktywacji nie stosuje się jendak po warstawch poolingowych, są to stałe operacje nie podlegające uczeniu.

W celu klasyfikacji obrazu musimy później użyć sieci MLP. Jako że wejściem do sieci MLP jest zawsze wektor, a wyjściem warstwy konwolucyjnej obraz. Musimy zatem obraz przetworzony przez filtry konwolucyjne sprowadzić do formy wektora, tzw. embedding-u / osadzenia, czyli reprezentacji obrazu jako punktu w pewnej ciągłej przestrzeni. Służy do tego warstwa spłaszczająca (flatten layer), rozwijająca macierze wielkowymiarowe na wektor, np $10 \times 10 \times 3$ na $300 \times 1$.

Część konwolucyjna nazywa się często backbone, a część MLP do klasyfikacji head. Głowa ma zwykle 1-2 warstwy w pełni połączone, z aktywacją softmax w ostatniej warstwie. Czasem jest nawet po prostu pojedynczą warstwą z softmaxem, bo w dużych sieciach konwolucyjnych ekstrakcja cech jest tak dobra, że taka prosta konstrukcja wystacza do klasyfikacji embeddingu.

In [1]:
import torch
import torchvision
import torchvision.transforms as transforms

Wybierzmy rodzaj akceleracji. Współczesne wersje PyTorch wspierają akcelerację nie tylko na kartach Nvidii i AMD, ale również na procesorach Apple z serii M. Obsługa AMD jest realizowana identycznie jak CUDA natomiast MPS (Apple) ma nieco inne API do sprawdzania dostępności i wybierania urządzenia. Zapisujemy wybrane urządzenie do zmiennej device, dzięki czemu w dalszych częściach kodu już nie będziemy musieli o tym myśleć.

In [2]:
if torch.cuda.is_available():
    device = torch.device("cuda:0")
elif torch.backends.mps.is_available():
    device = torch.device("mps")
else:
    device = torch.device('cpu')

print(device)
cpu

W pakiecie torchvision mamy funkcje automatycznie pobierające niektóre najbardziej popularne zbiory danych z obrazami.

W tym ćwiczeniu wykorzystamy zbiór FashionMNIST, który zawiera małe (28x28) zdjęcia ubrań w skali szarości. Zbiór ten został stworzony przez Zalando i jest "modowym" odpowiednikiem "cyferkowego" MNIST-a, jest z nim kompatybilny pod względem rozmiarów i charakterystyki danych, ale jest od MNIST-a trudniejszy w klasyfikacji.

Do funkcji ładujących zbiory danych możemy przekazać przekształcenie, które powinno zostać na nim wykonane. Przekształcenia można łączyć przy użyciu transforms.Compose. W tym przypadku przekonwertujemy dane z domyślnej reprezentacji PIL.Image na torch-owe tensory.

Pobrany dataset przekazujemy pod kontrolę DataLoader-a, który zajmuje się podawaniem danych w batch-ach podczas treningu.

In [3]:
transform = transforms.Compose([transforms.ToTensor()])

batch_size = 32

trainset = torchvision.datasets.FashionMNIST(
    root="./data", train=True, download=True, transform=transform
)
trainloader = torch.utils.data.DataLoader(
    trainset, batch_size=batch_size, shuffle=True
)

testset = torchvision.datasets.FashionMNIST(
    root="./data", train=False, download=True, transform=transform
)
testloader = torch.utils.data.DataLoader(
    testset, batch_size=batch_size, shuffle=True
)

classes = (
    "top",
    "Trouser",
    "Pullover",
    "Dress",
    "Coat",
    "Sandal",
    "Shirt",
    "Sneaker",
    "Bag",
    "Ankle boot",
)

print(type(testset[0][0]))
<class 'torch.Tensor'>

Zobaczmy, co jest w naszym zbiorze danych. Poniżej kawałek kodu, który wyświetli nam kilka przykładowych obrazków. Wartości pikseli są znormalizowane do przedziału [0,1].

In [4]:
import matplotlib.pyplot as plt
import numpy as np


def imshow(img):
    npimg = img.numpy()
    plt.imshow(np.transpose(npimg, (1, 2, 0)))
    plt.axis("off")
    plt.show()


dataiter = iter(trainloader)
images, labels = next(dataiter)

def grid_show(images, nrow=8):
    imshow(torchvision.utils.make_grid(images, nrow=nrow))


def print_grid(labels, nrow=8):
    rows = [labels[n : n + nrow] for n in range(0, len(labels), nrow)]
    for r in rows:
        print(" ".join(f"{classes[c]:10s}" for c in r))

grid_show(images)
print_grid(labels)
No description has been provided for this image
Bag        Pullover   Trouser    Dress      Sandal     Ankle boot Dress      Sneaker   
Coat       Pullover   Dress      Ankle boot Trouser    Pullover   Coat       Coat      
Shirt      Shirt      Bag        Dress      Dress      Shirt      Pullover   Trouser   
Dress      top        Shirt      Pullover   Ankle boot Shirt      top        Coat      

LeNet¶

LeNet to bardzo znany, klasyczny model sieci konwolucyjnej.

Warstwy:

  • obraz
  • konwolucja, kernel $5 \times 5$, bez paddingu, 6 kanałów (feature maps)
  • average pooling, kernel $2 \times 2$, stride 2
  • konwolucja, kernel $5 \times 5$, bez paddingu, 16 kanałów (feature maps)
  • average pooling, kernel $2 \times 2$, stride 2
  • warstwa w pełni połączona, 120 neuronów na wyjściu
  • warstwa w pełni połączona, 84 neurony na wyjściu
  • warstwa w pełni połączona, na wyjściu tyle neuronów, ile jest klas

Zadanie 1 (2 punkty)

Zaimplementuj wyżej opisaną sieć, używając biblioteki PyTorch. Wprowadzimy sobie jednak pewne modyfikacje, żeby było ciekawiej:

  • w pierwszej warstwie konwolucyjnej użyj 20 kanałów (feature maps)
  • w drugiej warstwie konwolucyjnej użyj 50 kanałów (feature maps)
  • w pierwszej warstwie gęstej użyj 300 neuronów
  • w drugiej warstwie gęstej użyj 100 neuronów

Przydatne elementy z pakietu torch.nn:

  • Conv2d()
  • AvgPool2d()
  • Linear()

Z pakietu torch.nn.functional:

  • relu()
In [5]:
import torch.nn as nn
import torch.nn.functional as F


class LeNet(nn.Module):
    def __init__(self):
        super().__init__()
        self.backbone = nn.Sequential(
            nn.Conv2d(in_channels=1, out_channels=20, kernel_size=5, padding=0),
            nn.ReLU(),

            nn.AvgPool2d(kernel_size=2, stride=2),

            nn.Conv2d(in_channels=20, out_channels=50, kernel_size=5, padding=0),
            nn.ReLU(),

            nn.AvgPool2d(kernel_size=2, stride=2),
        )

        self.head = nn.Sequential(
            nn.Linear(800, 300),
            nn.ReLU(),
            nn.Linear(300, len(classes)),
        )

        # your code here

    def forward(self, x):

        x = self.backbone(x)
        x = torch.flatten(x, 1)
        x = self.head(x)

        return x
    

# your_code

Do treningu użyjemy stochastycznego spadku po gradiencie (SGD), a jako funkcję straty Categorical Cross Entropy. W PyTorch-u funkcja ta operuje na indeksach klas (int), a nie na wektorach typu one-hot (jak w Tensorflow).

In [6]:
import torch.optim as optim

net = LeNet().to(device)

criterion = nn.CrossEntropyLoss()
optimizer = optim.SGD(net.parameters(), lr=0.001, momentum=0.9)

Zadanie 2 (1 punkt)

Uzupełnij pętlę uczącą sieć na podstawie jej predykcji. Oblicz (wykonaj krok do przodu) funkcję straty, a następnie przeprowadź propagację wsteczną i wykonaj krok optymalizatora.

In [33]:
trainloader

net.train()
print(len(trainloader))
for epoch in range(5):
# your_code
    for i, (X_batch, y_batch) in enumerate(trainloader):

        y_pred = net(X_batch)
        loss = criterion(y_pred, y_batch)

        optimizer.zero_grad()
        loss.backward()
        optimizer.step()

        if i % 100 == 0:
            print(f"Epoch {epoch}, batch: {i} train loss: {loss.item():.4f}")
net.eval()
1875
Epoch 0, batch: 0 train loss: 0.5358
Epoch 0, batch: 100 train loss: 0.4061
Epoch 0, batch: 200 train loss: 0.6641
Epoch 0, batch: 300 train loss: 0.5739
Epoch 0, batch: 400 train loss: 0.3948
Epoch 0, batch: 500 train loss: 0.6355
Epoch 0, batch: 600 train loss: 0.7601
Epoch 0, batch: 700 train loss: 0.5194
Epoch 0, batch: 800 train loss: 0.4207
Epoch 0, batch: 900 train loss: 0.4300
Epoch 0, batch: 1000 train loss: 0.3434
Epoch 0, batch: 1100 train loss: 0.4420
Epoch 0, batch: 1200 train loss: 0.7747
Epoch 0, batch: 1300 train loss: 0.6052
Epoch 0, batch: 1400 train loss: 0.6225
Epoch 0, batch: 1500 train loss: 0.5240
Epoch 0, batch: 1600 train loss: 0.4383
Epoch 0, batch: 1700 train loss: 0.6511
Epoch 0, batch: 1800 train loss: 0.4581
Epoch 1, batch: 0 train loss: 0.5192
Epoch 1, batch: 100 train loss: 0.5274
Epoch 1, batch: 200 train loss: 0.5369
Epoch 1, batch: 300 train loss: 0.5372
Epoch 1, batch: 400 train loss: 0.3746
Epoch 1, batch: 500 train loss: 0.4121
Epoch 1, batch: 600 train loss: 0.3309
Epoch 1, batch: 700 train loss: 0.4283
Epoch 1, batch: 800 train loss: 0.5030
Epoch 1, batch: 900 train loss: 0.3585
Epoch 1, batch: 1000 train loss: 0.5663
Epoch 1, batch: 1100 train loss: 0.5334
Epoch 1, batch: 1200 train loss: 0.4141
Epoch 1, batch: 1300 train loss: 0.2337
Epoch 1, batch: 1400 train loss: 0.4476
Epoch 1, batch: 1500 train loss: 0.5734
Epoch 1, batch: 1600 train loss: 0.1938
Epoch 1, batch: 1700 train loss: 0.4140
Epoch 1, batch: 1800 train loss: 0.3576
Epoch 2, batch: 0 train loss: 0.3614
Epoch 2, batch: 100 train loss: 0.6606
Epoch 2, batch: 200 train loss: 0.5088
Epoch 2, batch: 300 train loss: 0.3576
Epoch 2, batch: 400 train loss: 0.7534
Epoch 2, batch: 500 train loss: 0.6598
Epoch 2, batch: 600 train loss: 0.4704
Epoch 2, batch: 700 train loss: 0.5259
Epoch 2, batch: 800 train loss: 0.3127
Epoch 2, batch: 900 train loss: 0.3894
Epoch 2, batch: 1000 train loss: 0.3219
Epoch 2, batch: 1100 train loss: 0.4124
Epoch 2, batch: 1200 train loss: 0.6379
Epoch 2, batch: 1300 train loss: 0.5217
Epoch 2, batch: 1400 train loss: 0.4888
Epoch 2, batch: 1500 train loss: 0.4110
Epoch 2, batch: 1600 train loss: 0.4754
Epoch 2, batch: 1700 train loss: 0.3566
Epoch 2, batch: 1800 train loss: 0.4292
Epoch 3, batch: 0 train loss: 0.4026
Epoch 3, batch: 100 train loss: 0.4549
Epoch 3, batch: 200 train loss: 0.3717
Epoch 3, batch: 300 train loss: 0.3467
Epoch 3, batch: 400 train loss: 0.4052
Epoch 3, batch: 500 train loss: 0.3484
Epoch 3, batch: 600 train loss: 0.2663
Epoch 3, batch: 700 train loss: 0.6621
Epoch 3, batch: 800 train loss: 0.3212
Epoch 3, batch: 900 train loss: 0.4211
Epoch 3, batch: 1000 train loss: 0.2556
Epoch 3, batch: 1100 train loss: 0.3000
Epoch 3, batch: 1200 train loss: 0.2457
Epoch 3, batch: 1300 train loss: 0.4739
Epoch 3, batch: 1400 train loss: 0.3906
Epoch 3, batch: 1500 train loss: 0.3300
Epoch 3, batch: 1600 train loss: 0.2353
Epoch 3, batch: 1700 train loss: 0.3744
Epoch 3, batch: 1800 train loss: 0.2843
Epoch 4, batch: 0 train loss: 0.3719
Epoch 4, batch: 100 train loss: 0.2536
Epoch 4, batch: 200 train loss: 0.4361
Epoch 4, batch: 300 train loss: 0.3969
Epoch 4, batch: 400 train loss: 0.3334
Epoch 4, batch: 500 train loss: 0.4098
Epoch 4, batch: 600 train loss: 0.2931
Epoch 4, batch: 700 train loss: 0.4223
Epoch 4, batch: 800 train loss: 0.2724
Epoch 4, batch: 900 train loss: 0.3819
Epoch 4, batch: 1000 train loss: 0.4520
Epoch 4, batch: 1100 train loss: 0.3320
Epoch 4, batch: 1200 train loss: 0.2563
Epoch 4, batch: 1300 train loss: 0.3044
Epoch 4, batch: 1400 train loss: 0.4291
Epoch 4, batch: 1500 train loss: 0.3691
Epoch 4, batch: 1600 train loss: 0.3963
Epoch 4, batch: 1700 train loss: 0.5040
Epoch 4, batch: 1800 train loss: 0.4140
Out[33]:
LeNet(
  (backbone): Sequential(
    (0): Conv2d(1, 20, kernel_size=(5, 5), stride=(1, 1))
    (1): ReLU()
    (2): AvgPool2d(kernel_size=2, stride=2, padding=0)
    (3): Conv2d(20, 50, kernel_size=(5, 5), stride=(1, 1))
    (4): ReLU()
    (5): AvgPool2d(kernel_size=2, stride=2, padding=0)
  )
  (head): Sequential(
    (0): Linear(in_features=800, out_features=300, bias=True)
    (1): ReLU()
    (2): Linear(in_features=300, out_features=10, bias=True)
  )
)

Zobaczmy na kilku przykładach jak działa wytrenowana sieć.

In [34]:
dataiter = iter(testloader)
images, labels = next(dataiter)

grid_show(images)
print("Ground Truth")
print_grid(labels)

outputs = net(images.to(device))
_, predicted = torch.max(outputs, 1)

print()
print("Predicted")
print_grid(predicted)
No description has been provided for this image
Ground Truth
Trouser    Sneaker    Pullover   Dress      Pullover   Sneaker    Dress      Sneaker   
Coat       Trouser    Sandal     Shirt      top        Dress      Pullover   Shirt     
top        top        Dress      Shirt      Dress      Trouser    Pullover   Pullover  
Ankle boot Sandal     Ankle boot Bag        Ankle boot Sandal     Sandal     Sandal    

Predicted
top        Sneaker    Pullover   Dress      Shirt      Sneaker    Dress      Sneaker   
Coat       Trouser    Sandal     Shirt      top        Dress      Shirt      Shirt     
top        top        Dress      Pullover   Dress      Trouser    Coat       Shirt     
Ankle boot Sneaker    Ankle boot Bag        Ankle boot Sandal     Sandal     Sandal    

Obliczmy dokładności (accuracy) dla zbioru danych.

In [35]:
correct = 0
total = 0
net.eval()
with torch.no_grad():
    for data in testloader:
        images, labels = data
        outputs = net(images.to(device))
        _, predicted = torch.max(outputs.data, 1)
        total += labels.size(0)
        correct += (predicted == labels.to(device)).sum().item()

print(f"Accuracy of the network on the 10000 test images: {100 * correct // total} %")
Accuracy of the network on the 10000 test images: 84 %

Skomentuj wyniki:

  • Udało się otrzymać zadowalający wynik

Znając ogólny wynik klasyfikacji dla zbioru przeanalizujmy dokładniej, z którymi klasami jest największy problem.

Zadanie 3 (1 punkt)

Oblicz dokładność działania sieci (accuracy) dla każdej klasy z osobna. Podczas oceniania skuteczności modelu nie potrzebujemy, aby gradienty się liczyły. Możemy zatem zawrzeć obliczenia w bloku with torch.no_grad():

In [47]:
net.eval()

correct_predictions = {x: 0 for x in classes}
total_predictions = {x: 0 for x in classes}

with torch.no_grad():
    for data in testloader:
        images, labels = data
        outputs = net(images.to(device))
        _, predicted = torch.max(outputs.data, 1)

        for label, classname in enumerate(classes):
            class_pred = labels[labels == label] == predicted[labels == label]
            correct_predictions[classname] += class_pred.sum()
            total_predictions[classname] += len(class_pred)

accuracies = []

for classname, correct_count in correct_predictions.items():
    accuracies.append( (classname, 100 * float(correct_count) / total_predictions[classname]))

accuracies.sort(key=lambda x: x[1])

for classname, accuracy in accuracies:
    print(f"{accuracy:.2f}", classname, sep="\t")
41.00	Shirt
72.00	Pullover
83.20	Coat
84.00	Dress
90.10	top
91.90	Ankle boot
95.00	Sandal
95.90	Sneaker
96.20	Trouser
97.10	Bag

Skomentuj wyniki:

  • Najgorzej był rozpoznawany podkoszulek (Shirt), natomiast najlepiej była rozpoznawana torba (Bag)

Detekcja obiektów¶

Problem detekcji polega na nie tylko sklasyfikowaniu obiektów na obrazie, ale również wyznaczeniu jego dokładnego położenia w postaci bounding-box-u. Choć jest to problem odmienny od klasyfikacji obrazów, to w praktyce ściśle z nim powiązany - modele do detekcji obiektów przeważnie do pewnego momentu wyglądają tak samo, jak modele klasyfikacji. Jednak pod koniec sieć jest dzielona na 2 wyjścia: jedno to standardowa klasyfikacja, a drugie to regresor określający pozycję obiektu na obrazie, tzw. bounding box. Najpopularniejszymi przykładami takich sieci są YOLO i Mask R-CNN. Zbiór danych też jest odpowiednio przygotowany do tego zadania i oprócz właściwych zdjęć zawiera również listę bounding-box-ów i ich etykiety.

Zobaczymy jak działa detekcja na przykładzie już wytrenowanej sieci neuronowej. Autorzy skutecznych sieci często udostępniają ich wagi online, dzięki czemu jeżeli mamy doczynienia z analogicznym problemem jak ten, do którego dana sieć była przygotowana możemy z niej skorzystać "prosto z pudełka".

PyTorch pozwala nam na pobranie wytrenowanych wag dla kilku najpopularniejszych modeli. Sprawdzimy jak z tego skorzystać.

In [7]:
from torchvision.models import detection
import numpy as np
import cv2
from PIL import Image
import urllib

Poniżej znajduje się funkcja pozwalająca wczytać obraz z sieci. Przyda się do testowania działania sieci.

In [8]:
def url_to_image(url):
    resp = urllib.request.urlopen(url)
    image = np.asarray(bytearray(resp.read()), dtype="uint8")
    image = cv2.imdecode(image, cv2.IMREAD_COLOR)
    return image

Model, którym się zajmiemy to Faster R-CNN, który był trenowany na zbiorze COCO. Poniżej znajduje się lista klas (etykiet) dla tego zbioru danych.

In [9]:
classes = [
    "__background__",
    "person",
    "bicycle",
    "car",
    "motorcycle",
    "airplane",
    "bus",
    "train",
    "truck",
    "boat",
    "traffic light",
    "fire hydrant",
    "street sign",
    "stop sign",
    "parking meter",
    "bench",
    "bird",
    "cat",
    "dog",
    "horse",
    "sheep",
    "cow",
    "elephant",
    "bear",
    "zebra",
    "giraffe",
    "hat",
    "backpack",
    "umbrella",
    "handbag",
    "tie",
    "shoe",
    "eye glasses",
    "suitcase",
    "frisbee",
    "skis",
    "snowboard",
    "sports ball",
    "kite",
    "baseball bat",
    "baseball glove",
    "skateboard",
    "surfboard",
    "tennis racket",
    "bottle",
    "plate",
    "wine glass",
    "cup",
    "fork",
    "knife",
    "spoon",
    "bowl",
    "banana",
    "apple",
    "sandwich",
    "orange",
    "broccoli",
    "carrot",
    "hot dog",
    "pizza",
    "donut",
    "cake",
    "chair",
    "couch",
    "potted plant",
    "bed",
    "mirror",
    "dining table",
    "window",
    "desk",
    "toilet",
    "door",
    "tv",
    "laptop",
    "mouse",
    "remote",
    "keyboard",
    "cell phone",
    "microwave",
    "oven",
    "toaster",
    "sink",
    "refrigerator",
    "blender",
    "book",
    "clock",
    "vase",
    "scissors",
    "teddy bear",
    "hair drier",
    "toothbrush",
]

colors = np.random.randint(0, 256, size=(len(classes), 3))

Inizjalizacja modelu ResNet50-FPN wytrenowanymi wagami. Inicjalizujemy zarówno sieć backbone jak i RCNN.

In [10]:
model = detection.fasterrcnn_resnet50_fpn(
    weights=detection.FasterRCNN_ResNet50_FPN_Weights.DEFAULT,
    weights_backbone=torchvision.models.ResNet50_Weights.DEFAULT,
    progress=True,
    num_classes=len(classes)
).to(device)
model.eval()
Out[10]:
FasterRCNN(
  (transform): GeneralizedRCNNTransform(
      Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
      Resize(min_size=(800,), max_size=1333, mode='bilinear')
  )
  (backbone): BackboneWithFPN(
    (body): IntermediateLayerGetter(
      (conv1): Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False)
      (bn1): FrozenBatchNorm2d(64, eps=0.0)
      (relu): ReLU(inplace=True)
      (maxpool): MaxPool2d(kernel_size=3, stride=2, padding=1, dilation=1, ceil_mode=False)
      (layer1): Sequential(
        (0): Bottleneck(
          (conv1): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn1): FrozenBatchNorm2d(64, eps=0.0)
          (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
          (bn2): FrozenBatchNorm2d(64, eps=0.0)
          (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn3): FrozenBatchNorm2d(256, eps=0.0)
          (relu): ReLU(inplace=True)
          (downsample): Sequential(
            (0): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
            (1): FrozenBatchNorm2d(256, eps=0.0)
          )
        )
        (1): Bottleneck(
          (conv1): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn1): FrozenBatchNorm2d(64, eps=0.0)
          (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
          (bn2): FrozenBatchNorm2d(64, eps=0.0)
          (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn3): FrozenBatchNorm2d(256, eps=0.0)
          (relu): ReLU(inplace=True)
        )
        (2): Bottleneck(
          (conv1): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn1): FrozenBatchNorm2d(64, eps=0.0)
          (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
          (bn2): FrozenBatchNorm2d(64, eps=0.0)
          (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn3): FrozenBatchNorm2d(256, eps=0.0)
          (relu): ReLU(inplace=True)
        )
      )
      (layer2): Sequential(
        (0): Bottleneck(
          (conv1): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn1): FrozenBatchNorm2d(128, eps=0.0)
          (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
          (bn2): FrozenBatchNorm2d(128, eps=0.0)
          (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn3): FrozenBatchNorm2d(512, eps=0.0)
          (relu): ReLU(inplace=True)
          (downsample): Sequential(
            (0): Conv2d(256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False)
            (1): FrozenBatchNorm2d(512, eps=0.0)
          )
        )
        (1): Bottleneck(
          (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn1): FrozenBatchNorm2d(128, eps=0.0)
          (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
          (bn2): FrozenBatchNorm2d(128, eps=0.0)
          (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn3): FrozenBatchNorm2d(512, eps=0.0)
          (relu): ReLU(inplace=True)
        )
        (2): Bottleneck(
          (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn1): FrozenBatchNorm2d(128, eps=0.0)
          (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
          (bn2): FrozenBatchNorm2d(128, eps=0.0)
          (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn3): FrozenBatchNorm2d(512, eps=0.0)
          (relu): ReLU(inplace=True)
        )
        (3): Bottleneck(
          (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn1): FrozenBatchNorm2d(128, eps=0.0)
          (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
          (bn2): FrozenBatchNorm2d(128, eps=0.0)
          (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn3): FrozenBatchNorm2d(512, eps=0.0)
          (relu): ReLU(inplace=True)
        )
      )
      (layer3): Sequential(
        (0): Bottleneck(
          (conv1): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn1): FrozenBatchNorm2d(256, eps=0.0)
          (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
          (bn2): FrozenBatchNorm2d(256, eps=0.0)
          (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn3): FrozenBatchNorm2d(1024, eps=0.0)
          (relu): ReLU(inplace=True)
          (downsample): Sequential(
            (0): Conv2d(512, 1024, kernel_size=(1, 1), stride=(2, 2), bias=False)
            (1): FrozenBatchNorm2d(1024, eps=0.0)
          )
        )
        (1): Bottleneck(
          (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn1): FrozenBatchNorm2d(256, eps=0.0)
          (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
          (bn2): FrozenBatchNorm2d(256, eps=0.0)
          (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn3): FrozenBatchNorm2d(1024, eps=0.0)
          (relu): ReLU(inplace=True)
        )
        (2): Bottleneck(
          (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn1): FrozenBatchNorm2d(256, eps=0.0)
          (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
          (bn2): FrozenBatchNorm2d(256, eps=0.0)
          (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn3): FrozenBatchNorm2d(1024, eps=0.0)
          (relu): ReLU(inplace=True)
        )
        (3): Bottleneck(
          (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn1): FrozenBatchNorm2d(256, eps=0.0)
          (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
          (bn2): FrozenBatchNorm2d(256, eps=0.0)
          (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn3): FrozenBatchNorm2d(1024, eps=0.0)
          (relu): ReLU(inplace=True)
        )
        (4): Bottleneck(
          (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn1): FrozenBatchNorm2d(256, eps=0.0)
          (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
          (bn2): FrozenBatchNorm2d(256, eps=0.0)
          (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn3): FrozenBatchNorm2d(1024, eps=0.0)
          (relu): ReLU(inplace=True)
        )
        (5): Bottleneck(
          (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn1): FrozenBatchNorm2d(256, eps=0.0)
          (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
          (bn2): FrozenBatchNorm2d(256, eps=0.0)
          (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn3): FrozenBatchNorm2d(1024, eps=0.0)
          (relu): ReLU(inplace=True)
        )
      )
      (layer4): Sequential(
        (0): Bottleneck(
          (conv1): Conv2d(1024, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn1): FrozenBatchNorm2d(512, eps=0.0)
          (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
          (bn2): FrozenBatchNorm2d(512, eps=0.0)
          (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn3): FrozenBatchNorm2d(2048, eps=0.0)
          (relu): ReLU(inplace=True)
          (downsample): Sequential(
            (0): Conv2d(1024, 2048, kernel_size=(1, 1), stride=(2, 2), bias=False)
            (1): FrozenBatchNorm2d(2048, eps=0.0)
          )
        )
        (1): Bottleneck(
          (conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn1): FrozenBatchNorm2d(512, eps=0.0)
          (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
          (bn2): FrozenBatchNorm2d(512, eps=0.0)
          (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn3): FrozenBatchNorm2d(2048, eps=0.0)
          (relu): ReLU(inplace=True)
        )
        (2): Bottleneck(
          (conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn1): FrozenBatchNorm2d(512, eps=0.0)
          (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
          (bn2): FrozenBatchNorm2d(512, eps=0.0)
          (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn3): FrozenBatchNorm2d(2048, eps=0.0)
          (relu): ReLU(inplace=True)
        )
      )
    )
    (fpn): FeaturePyramidNetwork(
      (inner_blocks): ModuleList(
        (0): Conv2dNormActivation(
          (0): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1))
        )
        (1): Conv2dNormActivation(
          (0): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1))
        )
        (2): Conv2dNormActivation(
          (0): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1))
        )
        (3): Conv2dNormActivation(
          (0): Conv2d(2048, 256, kernel_size=(1, 1), stride=(1, 1))
        )
      )
      (layer_blocks): ModuleList(
        (0-3): 4 x Conv2dNormActivation(
          (0): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        )
      )
      (extra_blocks): LastLevelMaxPool()
    )
  )
  (rpn): RegionProposalNetwork(
    (anchor_generator): AnchorGenerator()
    (head): RPNHead(
      (conv): Sequential(
        (0): Conv2dNormActivation(
          (0): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
          (1): ReLU(inplace=True)
        )
      )
      (cls_logits): Conv2d(256, 3, kernel_size=(1, 1), stride=(1, 1))
      (bbox_pred): Conv2d(256, 12, kernel_size=(1, 1), stride=(1, 1))
    )
  )
  (roi_heads): RoIHeads(
    (box_roi_pool): MultiScaleRoIAlign(featmap_names=['0', '1', '2', '3'], output_size=(7, 7), sampling_ratio=2)
    (box_head): TwoMLPHead(
      (fc6): Linear(in_features=12544, out_features=1024, bias=True)
      (fc7): Linear(in_features=1024, out_features=1024, bias=True)
    )
    (box_predictor): FastRCNNPredictor(
      (cls_score): Linear(in_features=1024, out_features=91, bias=True)
      (bbox_pred): Linear(in_features=1024, out_features=364, bias=True)
    )
  )
)

IPython, z którego korzystamy w Jupyter Notebooku, ma wbudowaną funkcję display() do wyświetlania obrazów.

Do pobierania obrazów możemy się posłyżyć wget-em.

In [11]:
# Pobieranie obrazka z sieci
!wget https://upload.wikimedia.org/wikipedia/commons/thumb/7/7a/Toothbrush_x3_20050716_001.jpg/1280px-Toothbrush_x3_20050716_001.jpg --output-document toothbrushes.jpg
--2023-12-10 20:27:31--  https://upload.wikimedia.org/wikipedia/commons/thumb/7/7a/Toothbrush_x3_20050716_001.jpg/1280px-Toothbrush_x3_20050716_001.jpg
Resolving upload.wikimedia.org (upload.wikimedia.org)... 185.15.59.240
Connecting to upload.wikimedia.org (upload.wikimedia.org)|185.15.59.240|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 338300 (330K) [image/jpeg]
Saving to: 'toothbrushes.jpg'

     0K .......... .......... .......... .......... .......... 15%  985K 0s
    50K .......... .......... .......... .......... .......... 30% 2,07M 0s
   100K .......... .......... .......... .......... .......... 45% 3,20M 0s
   150K .......... .......... .......... .......... .......... 60% 4,04M 0s
   200K .......... .......... .......... .......... .......... 75% 4,59M 0s
   250K .......... .......... .......... .......... .......... 90% 4,18M 0s
   300K .......... .......... ..........                      100% 5,27M=0,1s

2023-12-10 20:27:31 (2,49 MB/s) - 'toothbrushes.jpg' saved [338300/338300]

In [12]:
# Wyświetlanie obrazka
image = Image.open("toothbrushes.jpg")
# make sure we have 3-channel RGB, e.g. without transparency
image = image.convert("RGB")
display(image)
No description has been provided for this image

PyTorch wymaga obrazów w kształcie [channels, height, width] (C, H, W) oraz z wartościami pikseli między 0 a 1. Pillow wczytuje obrazy z kanałami (H, W, C) oraz z wartościami pikseli między 0 a 255. Przed wykorzystaniem sieci neuronowej trzeba zatem:

  • zamienić obraz na tensor
  • zmienić kolejność kanałów
  • podzielić wartości pikseli przez 255
In [13]:
image_tensor = torch.from_numpy(np.array(image))
image_tensor = image_tensor.permute(2, 0, 1)
image_tensor_int = image_tensor  # useful for displaying, dtype = uint8
image_tensor = image_tensor / 255
image_tensor.shape, image_tensor.dtype
Out[13]:
(torch.Size([3, 960, 1280]), torch.float32)

Zadanie 4 (1 punkt)

Użyj modelu do wykrycia obiektów na obrazie. Następnie wybierz tylko te bounding boxy, dla których mamy wynik powyżej 50%. Wypisz te bounding boxy, ich prawdopodobieństwa (w procentach) oraz nazwy klas.

Następnie wykorzystaj wyniki do zaznaczenia bounding box'a dla każdego wykrytego obiektu na obrazie oraz podpisz wykrytą klasę wraz z prawdopodobieństwem. Możesz tutaj użyć:

  • OpenCV
  • PyTorch - Torchvision
In [57]:
# your_code
from torchvision.utils import draw_bounding_boxes
from torchvision.transforms import ToPILImage

with torch.no_grad():
    [results] = model([image_tensor.to(device)])

    boxes = results['boxes']
    labels = results['labels']
    scores = results['scores']

    score_condition = scores > .5

    picked_boxes = boxes[score_condition]
    picked_labels = labels[score_condition]
    picked_scores = scores[score_condition]

    result = np.array(image.copy())

    for i in range(len(picked_boxes)):
        box = picked_boxes[i]
        label = classes[picked_labels[i]]
        score = picked_scores[i]

        print(f'{score * 100:.2f}%\t{label}', box, sep="\t")

        frame_color = (0, 0, 255)
        result = cv2.rectangle(
            result,
            (int(box[0]), int(box[1])),
            (int(box[2]), int(box[3])),
            frame_color,
            2
        )

        cv2.putText(
            result, 
            f'{label}: {score * 100:.2f}%',
            (int(box[0]), int(box[1]) - 10), 
            cv2.FONT_HERSHEY_SIMPLEX, 
            0.9, 
            frame_color, 
            2
        )


    display(ToPILImage()(result))
94.17%	toothbrush	tensor([ 269.0258,  585.4758, 1246.7506,  715.8951])
88.41%	toothbrush	tensor([  90.0306,  266.9784, 1196.9512,  404.1362])
69.83%	spoon	tensor([ 601.2891,  456.0755, 1180.7574,  556.1579])
63.00%	toothbrush	tensor([ 617.2335,  586.1251, 1193.0754,  689.2254])
No description has been provided for this image

Fine-tuning i pretrening¶

Trenowanie głębokich sieci neuronowych do przetwarzania obrazów jest zadaniem wymagającym bardzo dużych zbiorów danych i zasobów obliczeniowych. Często jednak, nie musimy trenować takich sieci od nowa, możemy wykorzystać wytrenowane modele i jedynie dostosowywaać je do naszych problemów. Działanie takie nazywa się transfer learning-iem.

Przykładowao: mamy już wytrenowaną sieć na dużym zbiorze danych (pretrening) i chcemy, żeby sieć poradziła sobie z nową klasą obiektów (klasyfikacja), albo lepiej radziła sobie z wybranymi obiektami, które już zna (fine-tuning). Możemy usunąć ostatnią warstwę sieci i na jej miejsce wstawić nową, identyczną, jednak z losowo zainicjalizowanymi wagami, a następnie dotrenować sieć na naszym nowym, bardziej specyficznym zbiorze danych. Przykładowo, jako bazę weźmiemy model wytrenowany na zbiorze ImageNet i będziemy chcieli użyć go do rozpoznawania nowych, nieznanych mu klas, np. ras psów.

Dla przećwiczenia takiego schematu działania wykorzystamy zbiór danych z hotdogami. Będziemy chcieli stwierdzić, czy na obrazku jest hotdog, czy nie. Jako sieci użyjemy modelu ResNet-18, pretrenowanej na zbiorze ImageNet.

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# Download the hotdog dataset
!wget http://d2l-data.s3-accelerate.amazonaws.com/hotdog.zip
!unzip -n hotdog.zip
--2023-12-10 21:44:55--  http://d2l-data.s3-accelerate.amazonaws.com/hotdog.zip
Resolving d2l-data.s3-accelerate.amazonaws.com (d2l-data.s3-accelerate.amazonaws.com)... 18.244.103.202
Connecting to d2l-data.s3-accelerate.amazonaws.com (d2l-data.s3-accelerate.amazonaws.com)|18.244.103.202|:80... connected.
HTTP request sent, awaiting response... 200 OK
Length: 261292301 (249M) [application/zip]
Saving to: 'hotdog.zip'

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 12600K .......... .......... .......... .......... ..........  4%  260M 27s
 12650K .......... .......... .......... .......... ..........  4% 2,35M 27s
 12700K .......... .......... .......... .......... ..........  4% 80,3M 27s
 12750K .......... .......... .......... .......... ..........  5% 29,4M 27s
 12800K .......... .......... .......... .......... ..........  5% 36,8M 27s
 12850K .......... .......... .......... .......... ..........  5% 36,2M 27s
 12900K .......... .......... .......... .......... ..........  5% 83,4M 27s
 12950K .......... .......... .......... .......... ..........  5%  217M 27s
 13000K .......... .......... .......... .......... ..........  5%  954G 27s
 13050K .......... .......... .......... .......... ..........  5%  313M 26s
 13100K .......... .......... .......... .......... ..........  5% 76,2M 26s
 13150K .......... .......... .......... .......... ..........  5%  325M 26s
 13200K .......... .......... .......... .......... ..........  5%  954G 26s
 13250K .......... .......... .......... .......... ..........  5%  227M 26s
 13300K .......... .......... .......... .......... ..........  5%  146M 26s
 13350K .......... .......... .......... .......... ..........  5%  200M 26s
 13400K .......... .......... .......... .......... ..........  5%  376M 26s
 13450K .......... .......... .......... .......... ..........  5%  954G 26s
 13500K .......... .......... .......... .......... ..........  5%  350M 26s
 13550K .......... .......... .......... .......... ..........  5%  309M 26s
 13600K .......... .......... .......... .......... ..........  5%  307M 25s
 13650K .......... .......... .......... .......... ..........  5%  954G 25s
 13700K .......... .......... .......... .......... ..........  5%  329M 25s
 13750K .......... .......... .......... .......... ..........  5%  329M 25s
 13800K .......... .......... .......... .......... ..........  5%  177M 25s
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 13900K .......... .......... .......... .......... ..........  5%  954G 25s
 13950K .......... .......... .......... .......... ..........  5%  260M 25s
 14000K .......... .......... .......... .......... ..........  5%  219M 25s
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 14100K .......... .......... .......... .......... ..........  5%  954G 24s
 14150K .......... .......... .......... .......... ..........  5% 49,1M 24s
 14200K .......... .......... .......... .......... ..........  5% 88,1M 24s
 14250K .......... .......... .......... .......... ..........  5% 94,2M 24s
 14300K .......... .......... .......... .......... ..........  5%  108M 24s
 14350K .......... .......... .......... .......... ..........  5% 62,4M 24s
 14400K .......... .......... .......... .......... ..........  5%  118M 24s
 14450K .......... .......... .......... .......... ..........  5% 94,2M 24s
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 14550K .......... .......... .......... .......... ..........  5%  103M 24s
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 14650K .......... .......... .......... .......... ..........  5%  106M 24s
 14700K .......... .......... .......... .......... ..........  5%  102M 24s
 14750K .......... .......... .......... .......... ..........  5% 81,2M 23s
 14800K .......... .......... .......... .......... ..........  5% 13,2M 23s
 14850K .......... .......... .......... .......... ..........  5%  112M 23s
 14900K .......... .......... .......... .......... ..........  5% 50,6M 23s
 14950K .......... .......... .......... .......... ..........  5% 11,3M 23s
 15000K .......... .......... .......... .......... ..........  5% 37,6M 23s
 15050K .......... .......... .......... .......... ..........  5% 32,5M 23s
 15100K .......... .......... .......... .......... ..........  5% 24,4M 23s
 15150K .......... .......... .......... .......... ..........  5% 28,1M 23s
 15200K .......... .......... .......... .......... ..........  5% 32,3M 23s
 15250K .......... .......... .......... .......... ..........  5% 52,0M 23s
 15300K .......... .......... .......... .......... ..........  6% 40,0M 23s
 15350K .......... .......... .......... .......... ..........  6% 33,7M 23s
 15400K .......... .......... .......... .......... ..........  6% 35,9M 23s
 15450K .......... .......... .......... .......... ..........  6% 16,4M 23s
 15500K .......... .......... .......... .......... ..........  6% 44,7M 23s
 15550K .......... .......... .......... .......... ..........  6% 15,5M 23s
 15600K .......... .......... .......... .......... ..........  6% 32,7M 23s
 15650K .......... .......... .......... .......... ..........  6% 31,6M 23s
 15700K .......... .......... .......... .......... ..........  6% 39,8M 22s
 15750K .......... .......... .......... .......... ..........  6% 40,5M 22s
 15800K .......... .......... .......... .......... ..........  6% 19,3M 22s
 15850K .......... .......... .......... .......... ..........  6% 40,3M 22s
 15900K .......... .......... .......... .......... ..........  6% 20,4M 22s
 15950K .......... .......... .......... .......... ..........  6% 32,1M 22s
 16000K .......... .......... .......... .......... ..........  6% 27,8M 22s
 16050K .......... .......... .......... .......... ..........  6% 40,4M 22s
 16100K .......... .......... .......... .......... ..........  6% 28,6M 22s
 16150K .......... .......... .......... .......... ..........  6% 53,7M 22s
 16200K .......... .......... .......... .......... ..........  6% 1,78M 22s
 16250K .......... .......... .......... .......... ..........  6%  954G 22s
 16300K .......... .......... .......... .......... ..........  6%  280M 22s
 16350K .......... .......... .......... .......... ..........  6%  396M 22s
 16400K .......... .......... .......... .......... ..........  6%  168M 22s
 16450K .......... .......... .......... .......... ..........  6%  954G 22s
 16500K .......... .......... .......... .......... ..........  6%  368M 22s
 16550K .......... .......... .......... .......... ..........  6%  358M 22s
 16600K .......... .......... .......... .......... ..........  6%  321M 22s
 16650K .......... .......... .......... .......... ..........  6%  315M 22s
 16700K .......... .......... .......... .......... ..........  6%  954G 22s
 16750K .......... .......... .......... .......... ..........  6%  323M 22s
 16800K .......... .......... .......... .......... ..........  6%  101M 22s
 16850K .......... .......... .......... .......... ..........  6%  122M 21s
 16900K .......... .......... .......... .......... ..........  6%  204M 21s
 16950K .......... .......... .......... .......... ..........  6% 31,7M 21s
 17000K .......... .......... .......... .......... ..........  6%  111M 21s
 17050K .......... .......... .......... .......... ..........  6% 25,3M 21s
 17100K .......... .......... .......... .......... ..........  6% 27,8M 21s
 17150K .......... .......... .......... .......... ..........  6% 45,8M 21s
 17200K .......... .......... .......... .......... ..........  6% 41,8M 21s
 17250K .......... .......... .......... .......... ..........  6% 39,2M 21s
 17300K .......... .......... .......... .......... ..........  6% 21,7M 21s
 17350K .......... .......... .......... .......... ..........  6% 22,3M 21s
 17400K .......... .......... .......... .......... ..........  6% 24,0M 21s
 17450K .......... .......... .......... .......... ..........  6% 17,5M 21s
 17500K .......... .......... .......... .......... ..........  6% 99,7M 21s
 17550K .......... .......... .......... .......... ..........  6% 20,5M 21s
 17600K .......... .......... .......... .......... ..........  6% 35,6M 21s
 17650K .......... .......... .......... .......... ..........  6% 32,3M 21s
 17700K .......... .......... .......... .......... ..........  6% 30,8M 21s
 17750K .......... .......... .......... .......... ..........  6% 29,9M 21s
 17800K .......... .......... .......... .......... ..........  6% 40,6M 21s
 17850K .......... .......... .......... .......... ..........  7% 7,20M 21s
 17900K .......... .......... .......... .......... ..........  7% 41,6M 21s
 17950K .......... .......... .......... .......... ..........  7% 79,0M 21s
 18000K .......... .......... .......... .......... ..........  7% 22,2M 21s
 18050K .......... .......... .......... .......... ..........  7% 30,6M 20s
 18100K .......... .......... .......... .......... ..........  7% 41,0M 20s
 18150K .......... .......... .......... .......... ..........  7% 17,6M 20s
 18200K .......... .......... .......... .......... ..........  7% 40,3M 20s
 18250K .......... .......... .......... .......... ..........  7% 38,0M 20s
 18300K .......... .......... .......... .......... ..........  7% 37,1M 20s
 18350K .......... .......... .......... .......... ..........  7% 17,3M 20s
 18400K .......... .......... .......... .......... ..........  7% 68,7M 20s
 18450K .......... .......... .......... .......... ..........  7% 20,8M 20s
 18500K .......... .......... .......... .......... ..........  7% 33,9M 20s
 18550K .......... .......... .......... .......... ..........  7% 45,1M 20s
 18600K .......... .......... .......... .......... ..........  7% 37,6M 20s
 18650K .......... .......... .......... .......... ..........  7% 25,1M 20s
 18700K .......... .......... .......... .......... ..........  7% 1,44M 20s
 18750K .......... .......... .......... .......... ..........  7% 71,4M 20s
 18800K .......... .......... .......... .......... ..........  7% 32,1M 20s
 18850K .......... .......... .......... .......... ..........  7%  121M 20s
 18900K .......... .......... .......... .......... ..........  7% 9,02M 20s
 18950K .......... .......... .......... .......... ..........  7%  954G 20s
 19000K .......... .......... .......... .......... ..........  7% 69,7M 20s
 19050K .......... .......... .......... .......... ..........  7%  247M 20s
 19100K .......... .......... .......... .......... ..........  7%  277M 20s
 19150K .......... .......... .......... .......... ..........  7%  274M 20s
 19200K .......... .......... .......... .......... ..........  7%  954G 20s
 19250K .......... .......... .......... .......... ..........  7%  258M 20s
 19300K .......... .......... .......... .......... ..........  7%  280M 20s
 19350K .......... .......... .......... .......... ..........  7% 4,72M 20s
 19400K .......... .......... .......... .......... ..........  7%  110M 20s
 19450K .......... .......... .......... .......... ..........  7% 28,2M 20s
 19500K .......... .......... .......... .......... ..........  7% 72,2M 20s
 19550K .......... .......... .......... .......... ..........  7% 2,79M 20s
 19600K .......... .......... .......... .......... ..........  7%  158M 20s
 19650K .......... .......... .......... .......... ..........  7% 67,4M 20s
 19700K .......... .......... .......... .......... ..........  7% 14,5M 20s
 19750K .......... .......... .......... .......... ..........  7%  306M 20s
 19800K .......... .......... .......... .......... ..........  7% 33,4M 20s
 19850K .......... .......... .......... .......... ..........  7% 6,98M 20s
 19900K .......... .......... .......... .......... ..........  7% 48,8M 20s
 19950K .......... .......... .......... .......... ..........  7%  146M 20s
 20000K .......... .......... .......... .......... ..........  7%  176M 20s
 20050K .......... .......... .......... .......... ..........  7%  954G 20s
 20100K .......... .......... .......... .......... ..........  7%  260M 20s
 20150K .......... .......... .......... .......... ..........  7%  239M 19s
 20200K .......... .......... .......... .......... ..........  7%  289M 19s
 20250K .......... .......... .......... .......... ..........  7%  301M 19s
 20300K .......... .......... .......... .......... ..........  7%  954G 19s
 20350K .......... .......... .......... .......... ..........  7%  121M 19s
 20400K .......... .......... .......... .......... ..........  8% 68,8M 19s
 20450K .......... .......... .......... .......... ..........  8% 98,4M 19s
 20500K .......... .......... .......... .......... ..........  8%  954G 19s
 20550K .......... .......... .......... .......... ..........  8%  203M 19s
 20600K .......... .......... .......... .......... ..........  8%  131M 19s
 20650K .......... .......... .......... .......... ..........  8%  108M 19s
 20700K .......... .......... .......... .......... ..........  8%  126M 19s
 20750K .......... .......... .......... .......... ..........  8%  954G 19s
 20800K .......... .......... .......... .......... ..........  8% 99,4M 19s
 20850K .......... .......... .......... .......... ..........  8%  188M 19s
 20900K .......... .......... .......... .......... ..........  8%  184M 19s
 20950K .......... .......... .......... .......... ..........  8%  217M 19s
 21000K .......... .......... .......... .......... ..........  8%  954G 19s
 21050K .......... .......... .......... .......... ..........  8%  266M 19s
 21100K .......... .......... .......... .......... ..........  8%  334M 19s
 21150K .......... .......... .......... .......... ..........  8%  122M 19s
 21200K .......... .......... .......... .......... ..........  8% 52,3M 18s
 21250K .......... .......... .......... .......... ..........  8% 55,7M 18s
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 21400K .......... .......... .......... .......... ..........  8% 24,3M 18s
 21450K .......... .......... .......... .......... ..........  8% 3,43M 18s
 21500K .......... .......... .......... .......... ..........  8% 93,2M 18s
 21550K .......... .......... .......... .......... ..........  8% 81,7M 18s
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 21650K .......... .......... .......... .......... ..........  8% 86,1M 18s
 21700K .......... .......... .......... .......... ..........  8%  145M 18s
 21750K .......... .......... .......... .......... ..........  8%  103M 18s
 21800K .......... .......... .......... .......... ..........  8% 62,2M 18s
 21850K .......... .......... .......... .......... ..........  8%  148M 18s
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 21950K .......... .......... .......... .......... ..........  8% 68,3M 18s
 22000K .......... .......... .......... .......... ..........  8% 18,4M 18s
 22050K .......... .......... .......... .......... ..........  8% 20,2M 18s
 22100K .......... .......... .......... .......... ..........  8% 43,6M 18s
 22150K .......... .......... .......... .......... ..........  8% 40,9M 18s
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 22250K .......... .......... .......... .......... ..........  8% 32,4M 18s
 22300K .......... .......... .......... .......... ..........  8% 41,7M 18s
 22350K .......... .......... .......... .......... ..........  8% 29,3M 18s
 22400K .......... .......... .......... .......... ..........  8% 41,9M 18s
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 22500K .......... .......... .......... .......... ..........  8% 69,3M 18s
 22550K .......... .......... .......... .......... ..........  8% 25,3M 18s
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 22650K .......... .......... .......... .......... ..........  8% 59,5M 18s
 22700K .......... .......... .......... .......... ..........  8%  166M 18s
 22750K .......... .......... .......... .......... ..........  8% 23,1M 18s
 22800K .......... .......... .......... .......... ..........  8% 37,3M 18s
 22850K .......... .......... .......... .......... ..........  8% 14,6M 18s
 22900K .......... .......... .......... .......... ..........  8% 53,5M 18s
 22950K .......... .......... .......... .......... ..........  9% 18,4M 18s
 23000K .......... .......... .......... .......... ..........  9% 34,5M 18s
 23050K .......... .......... .......... .......... ..........  9% 17,4M 18s
 23100K .......... .......... .......... .......... ..........  9% 39,3M 17s
 23150K .......... .......... .......... .......... ..........  9% 31,2M 17s
 23200K .......... .......... .......... .......... ..........  9% 1,17M 18s
 23250K .......... .......... .......... .......... ..........  9% 3,32M 18s
 23300K .......... .......... .......... .......... ..........  9%  954G 18s
 23350K .......... .......... .......... .......... ..........  9% 19,4M 18s
 23400K .......... .......... .......... .......... ..........  9% 19,4M 18s
 23450K .......... .......... .......... .......... ..........  9%  954G 18s
 23500K .......... .......... .......... .......... ..........  9% 49,0M 18s
 23550K .......... .......... .......... .......... ..........  9% 28,9M 18s
 23600K .......... .......... .......... .......... ..........  9%  954G 18s
 23650K .......... .......... .......... .......... ..........  9% 22,1M 18s
 23700K .......... .......... .......... .......... ..........  9% 60,6M 18s
 23750K .......... .......... .......... .......... ..........  9%  305M 18s
 23800K .......... .......... .......... .......... ..........  9% 41,1M 18s
 23850K .......... .......... .......... .......... ..........  9% 11,1M 18s
 23900K .......... .......... .......... .......... ..........  9%  338M 18s
 23950K .......... .......... .......... .......... ..........  9% 12,3M 18s
 24000K .......... .......... .......... .......... ..........  9% 34,4M 18s
 24050K .......... .......... .......... .......... ..........  9% 28,6M 18s
 24100K .......... .......... .......... .......... ..........  9% 30,5M 17s
 24150K .......... .......... .......... .......... ..........  9%  134M 17s
 24200K .......... .......... .......... .......... ..........  9% 77,5M 17s
 24250K .......... .......... .......... .......... ..........  9% 40,2M 17s
 24300K .......... .......... .......... .......... ..........  9% 26,0M 17s
 24350K .......... .......... .......... .......... ..........  9% 43,7M 17s
 24400K .......... .......... .......... .......... ..........  9% 32,4M 17s
 24450K .......... .......... .......... .......... ..........  9%  954G 17s
 24500K .......... .......... .......... .......... ..........  9%  271M 17s
 24550K .......... .......... .......... .......... ..........  9%  163M 17s
 24600K .......... .......... .......... .......... ..........  9%  254M 17s
 24650K .......... .......... .......... .......... ..........  9%  954G 17s
 24700K .......... .......... .......... .......... ..........  9%  338M 17s
 24750K .......... .......... .......... .......... ..........  9%  372M 17s
 24800K .......... .......... .......... .......... ..........  9%  388M 17s
 24850K .......... .......... .......... .......... ..........  9%  389M 17s
 24900K .......... .......... .......... .......... ..........  9%  954G 17s
 24950K .......... .......... .......... .......... ..........  9%  391M 17s
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 25050K .......... .......... .......... .......... ..........  9%  325M 17s
 25100K .......... .......... .......... .......... ..........  9%  332M 17s
 25150K .......... .......... .......... .......... ..........  9%  954G 17s
 25200K .......... .......... .......... .......... ..........  9%  364M 17s
 25250K .......... .......... .......... .......... ..........  9%  394M 17s
 25300K .......... .......... .......... .......... ..........  9%  367M 17s
 25350K .......... .......... .......... .......... ..........  9%  954G 17s
 25400K .......... .......... .......... .......... ..........  9%  327M 17s
 25450K .......... .......... .......... .......... ..........  9%  235M 17s
 25500K .......... .......... .......... .......... .......... 10%  111M 17s
 25550K .......... .......... .......... .......... .......... 10%  279M 16s
 25600K .......... .......... .......... .......... .......... 10%  954G 16s
 25650K .......... .......... .......... .......... .......... 10%  237M 16s
 25700K .......... .......... .......... .......... .......... 10% 9,46M 16s
 25750K .......... .......... .......... .......... .......... 10%  119M 16s
 25800K .......... .......... .......... .......... .......... 10%  285M 16s
 25850K .......... .......... .......... .......... .......... 10%  169M 16s
 25900K .......... .......... .......... .......... .......... 10%  137M 16s
 25950K .......... .......... .......... .......... .......... 10% 11,4M 16s
 26000K .......... .......... .......... .......... .......... 10% 74,7M 16s
 26050K .......... .......... .......... .......... .......... 10%  172M 16s
 26100K .......... .......... .......... .......... .......... 10%  137M 16s
 26150K .......... .......... .......... .......... .......... 10% 80,2M 16s
 26200K .......... .......... .......... .......... .......... 10% 69,9M 16s
 26250K .......... .......... .......... .......... .......... 10% 32,4M 16s
 26300K .......... .......... .......... .......... .......... 10% 17,9M 16s
 26350K .......... .......... .......... .......... .......... 10% 21,0M 16s
 26400K .......... .......... .......... .......... .......... 10% 51,0M 16s
 26450K .......... .......... .......... .......... .......... 10% 28,8M 16s
 26500K .......... .......... .......... .......... .......... 10% 24,1M 16s
 26550K .......... .......... .......... .......... .......... 10% 16,0M 16s
 26600K .......... .......... .......... .......... .......... 10% 29,8M 16s
 26650K .......... .......... .......... .......... .......... 10% 31,9M 16s
 26700K .......... .......... .......... .......... .......... 10% 26,5M 16s
 26750K .......... .......... .......... .......... .......... 10% 16,8M 16s
 26800K .......... .......... .......... .......... .......... 10% 38,4M 16s
 26850K .......... .......... .......... .......... .......... 10% 21,0M 16s
 26900K .......... .......... .......... .......... .......... 10% 42,6M 16s
 26950K .......... .......... .......... .......... .......... 10% 40,5M 16s
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 27050K .......... .......... .......... .......... .......... 10% 26,2M 16s
 27100K .......... .......... .......... .......... .......... 10% 40,3M 16s
 27150K .......... .......... .......... .......... .......... 10% 38,9M 16s
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 27250K .......... .......... .......... .......... .......... 10% 3,28M 16s
 27300K .......... .......... .......... .......... .......... 10% 99,2M 16s
 27350K .......... .......... .......... .......... .......... 10% 87,4M 16s
 27400K .......... .......... .......... .......... .......... 10%  101M 16s
 27450K .......... .......... .......... .......... .......... 10% 81,9M 16s
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 27700K .......... .......... .......... .......... .......... 10% 93,6M 16s
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 27800K .......... .......... .......... .......... .......... 10% 88,9M 16s
 27850K .......... .......... .......... .......... .......... 10% 68,3M 16s
 27900K .......... .......... .......... .......... .......... 10% 73,6M 16s
 27950K .......... .......... .......... .......... .......... 10% 38,0M 16s
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 28050K .......... .......... .......... .......... .......... 11% 18,0M 15s
 28100K .......... .......... .......... .......... .......... 11% 39,3M 15s
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 28200K .......... .......... .......... .......... .......... 11% 41,3M 15s
 28250K .......... .......... .......... .......... .......... 11% 27,6M 15s
 28300K .......... .......... .......... .......... .......... 11% 46,5M 15s
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 28850K .......... .......... .......... .......... .......... 11% 16,2M 15s
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 29050K .......... .......... .......... .......... .......... 11% 48,9M 15s
 29100K .......... .......... .......... .......... .......... 11% 33,1M 15s
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 29250K .......... .......... .......... .......... .......... 11%  967K 15s
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 29350K .......... .......... .......... .......... .......... 11% 11,5M 15s
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 29650K .......... .......... .......... .......... .......... 11% 77,1M 15s
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 30100K .......... .......... .......... .......... .......... 11% 51,2M 15s
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 30300K .......... .......... .......... .......... .......... 11% 13,6M 15s
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 31950K .......... .......... .......... .......... .......... 12% 47,7M 14s
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 32150K .......... .......... .......... .......... .......... 12% 14,8M 14s
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 34050K .......... .......... .......... .......... .......... 13% 66,2M 14s
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 34600K .......... .......... .......... .......... .......... 13% 75,3M 14s
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 36150K .......... .......... .......... .......... .......... 14% 29,7M 13s
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 36550K .......... .......... .......... .......... .......... 14% 65,4M 13s
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 37150K .......... .......... .......... .......... .......... 14%  188M 13s
 37200K .......... .......... .......... .......... .......... 14% 17,9M 13s
 37250K .......... .......... .......... .......... .......... 14% 53,2M 13s
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 37700K .......... .......... .......... .......... .......... 14% 18,0M 13s
 37750K .......... .......... .......... .......... .......... 14% 33,6M 13s
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 37900K .......... .......... .......... .......... .......... 14% 75,1M 13s
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 38050K .......... .......... .......... .......... .......... 14%  954G 13s
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 38200K .......... .......... .......... .......... .......... 14% 21,1M 13s
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 38300K .......... .......... .......... .......... .......... 15% 63,8M 13s
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 40000K .......... .......... .......... .......... .......... 15% 29,6M 13s
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 40100K .......... .......... .......... .......... .......... 15% 19,3M 13s
 40150K .......... .......... .......... .......... .......... 15% 27,9M 13s
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 40300K .......... .......... .......... .......... .......... 15% 20,9M 12s
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 40700K .......... .......... .......... .......... .......... 15% 36,9M 12s
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 40800K .......... .......... .......... .......... .......... 16% 42,3M 12s
 40850K .......... .......... .......... .......... .......... 16% 34,9M 12s
 40900K .......... .......... .......... .......... .......... 16% 18,9M 12s
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 41000K .......... .......... .......... .......... .......... 16% 1,19M 13s
 41050K .......... .......... .......... .......... .......... 16% 7,95M 13s
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 41200K .......... .......... .......... .......... .......... 16%  345M 13s
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 41450K .......... .......... .......... .......... .......... 16% 92,6M 13s
 41500K .......... .......... .......... .......... .......... 16% 30,4M 13s
 41550K .......... .......... .......... .......... .......... 16%  258M 13s
 41600K .......... .......... .......... .......... .......... 16% 25,7M 13s
 41650K .......... .......... .......... .......... .......... 16% 94,6M 13s
 41700K .......... .......... .......... .......... .......... 16%  151M 12s
 41750K .......... .......... .......... .......... .......... 16% 81,0M 12s
 41800K .......... .......... .......... .......... .......... 16%  120M 12s
 41850K .......... .......... .......... .......... .......... 16%  169M 12s
 41900K .......... .......... .......... .......... .......... 16% 61,8M 12s
 41950K .......... .......... .......... .......... .......... 16% 36,4M 12s
 42000K .......... .......... .......... .......... .......... 16% 18,0M 12s
 42050K .......... .......... .......... .......... .......... 16%  181M 12s
 42100K .......... .......... .......... .......... .......... 16%  954G 12s
 42150K .......... .......... .......... .......... .......... 16%  398M 12s
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 42250K .......... .......... .......... .......... .......... 16% 8,24M 12s
 42300K .......... .......... .......... .......... .......... 16% 32,4M 12s
 42350K .......... .......... .......... .......... .......... 16% 49,9M 12s
 42400K .......... .......... .......... .......... .......... 16%  197M 12s
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 42600K .......... .......... .......... .......... .......... 16%  249M 12s
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 43050K .......... .......... .......... .......... .......... 16%  132M 12s
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 43150K .......... .......... .......... .......... .......... 16%  240M 12s
 43200K .......... .......... .......... .......... .......... 16% 11,1M 12s
 43250K .......... .......... .......... .......... .......... 16% 31,5M 12s
 43300K .......... .......... .......... .......... .......... 16% 44,5M 12s
 43350K .......... .......... .......... .......... .......... 17% 29,6M 12s
 43400K .......... .......... .......... .......... .......... 17% 15,4M 12s
 43450K .......... .......... .......... .......... .......... 17% 42,9M 12s
 43500K .......... .......... .......... .......... .......... 17% 7,45M 12s
 43550K .......... .......... .......... .......... .......... 17% 29,9M 12s
 43600K .......... .......... .......... .......... .......... 17% 31,4M 12s
 43650K .......... .......... .......... .......... .......... 17% 39,5M 12s
 43700K .......... .......... .......... .......... .......... 17% 39,4M 12s
 43750K .......... .......... .......... .......... .......... 17% 39,1M 12s
 43800K .......... .......... .......... .......... .......... 17% 47,9M 12s
 43850K .......... .......... .......... .......... .......... 17% 1,02M 12s
 43900K .......... .......... .......... .......... .......... 17% 16,1M 12s
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 44000K .......... .......... .......... .......... .......... 17% 86,8M 12s
 44050K .......... .......... .......... .......... .......... 17% 24,0M 12s
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 44150K .......... .......... .......... .......... .......... 17%  387M 12s
 44200K .......... .......... .......... .......... .......... 17% 10,9M 12s
 44250K .......... .......... .......... .......... .......... 17% 23,3M 12s
 44300K .......... .......... .......... .......... .......... 17% 81,5M 12s
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 44500K .......... .......... .......... .......... .......... 17% 12,9M 12s
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 44700K .......... .......... .......... .......... .......... 17% 10,7M 12s
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 44800K .......... .......... .......... .......... .......... 17% 13,2M 12s
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 44950K .......... .......... .......... .......... .......... 17%  954G 12s
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 45200K .......... .......... .......... .......... .......... 17%  954G 12s
 45250K .......... .......... .......... .......... .......... 17%  242M 12s
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 45900K .......... .......... .......... .......... .......... 18%  299M 12s
 45950K .......... .......... .......... .......... .......... 18% 72,0M 12s
 46000K .......... .......... .......... .......... .......... 18% 38,4M 12s
 46050K .......... .......... .......... .......... .......... 18% 22,6M 12s
 46100K .......... .......... .......... .......... .......... 18% 10,2M 12s
 46150K .......... .......... .......... .......... .......... 18% 39,4M 12s
 46200K .......... .......... .......... .......... .......... 18% 19,6M 12s
 46250K .......... .......... .......... .......... .......... 18% 26,4M 12s
 46300K .......... .......... .......... .......... .......... 18% 41,2M 12s
 46350K .......... .......... .......... .......... .......... 18% 39,8M 12s
 46400K .......... .......... .......... .......... .......... 18% 35,1M 12s
 46450K .......... .......... .......... .......... .......... 18% 41,2M 12s
 46500K .......... .......... .......... .......... .......... 18% 31,1M 12s
 46550K .......... .......... .......... .......... .......... 18%  888K 12s
 46600K .......... .......... .......... .......... .......... 18% 7,30M 12s
 46650K .......... .......... .......... .......... .......... 18%  954G 12s
 46700K .......... .......... .......... .......... .......... 18%  262M 12s
 46750K .......... .......... .......... .......... .......... 18%  382M 12s
 46800K .......... .......... .......... .......... .......... 18%  408M 12s
 46850K .......... .......... .......... .......... .......... 18%  218M 12s
 46900K .......... .......... .......... .......... .......... 18% 8,36M 12s
 46950K .......... .......... .......... .......... .......... 18%  954G 12s
 47000K .......... .......... .......... .......... .......... 18%  217M 12s
 47050K .......... .......... .......... .......... .......... 18%  362M 12s
 47100K .......... .......... .......... .......... .......... 18% 9,36M 12s
 47150K .......... .......... .......... .......... .......... 18% 34,2M 12s
 47200K .......... .......... .......... .......... .......... 18% 97,4M 12s
 47250K .......... .......... .......... .......... .......... 18%  144M 12s
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 47350K .......... .......... .......... .......... .......... 18%  954G 12s
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 47600K .......... .......... .......... .......... .......... 18%  954G 12s
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 47750K .......... .......... .......... .......... .......... 18% 5,04M 12s
 47800K .......... .......... .......... .......... .......... 18% 39,9M 12s
 47850K .......... .......... .......... .......... .......... 18%  954G 12s
 47900K .......... .......... .......... .......... .......... 18% 81,9M 12s
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 48450K .......... .......... .......... .......... .......... 19%  236M 11s
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 48750K .......... .......... .......... .......... .......... 19% 74,9M 11s
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 48850K .......... .......... .......... .......... .......... 19%  109M 11s
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 49050K .......... .......... .......... .......... .......... 19% 62,5M 12s
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 50150K .......... .......... .......... .......... .......... 19% 18,3M 11s
 50200K .......... .......... .......... .......... .......... 19% 63,2M 11s
 50250K .......... .......... .......... .......... .......... 19% 36,8M 11s
 50300K .......... .......... .......... .......... .......... 19% 58,9M 11s
 50350K .......... .......... .......... .......... .......... 19%  954G 11s
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 50850K .......... .......... .......... .......... .......... 19%  239M 11s
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 50950K .......... .......... .......... .......... .......... 19% 99,8M 11s
 51000K .......... .......... .......... .......... .......... 20% 51,5M 11s
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 51100K .......... .......... .......... .......... .......... 20% 53,8M 11s
 51150K .......... .......... .......... .......... .......... 20% 71,0M 11s
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 51500K .......... .......... .......... .......... .......... 20% 33,7M 11s
 51550K .......... .......... .......... .......... .......... 20% 43,3M 11s
 51600K .......... .......... .......... .......... .......... 20% 36,2M 11s
 51650K .......... .......... .......... .......... .......... 20% 33,0M 11s
 51700K .......... .......... .......... .......... .......... 20% 14,2M 11s
 51750K .......... .......... .......... .......... .......... 20% 26,5M 11s
 51800K .......... .......... .......... .......... .......... 20% 6,59M 11s
 51850K .......... .......... .......... .......... .......... 20% 19,4M 11s
 51900K .......... .......... .......... .......... .......... 20% 38,2M 11s
 51950K .......... .......... .......... .......... .......... 20% 22,4M 11s
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 52050K .......... .......... .......... .......... .......... 20% 96,8M 11s
 52100K .......... .......... .......... .......... .......... 20%  113M 11s
 52150K .......... .......... .......... .......... .......... 20% 65,1M 11s
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 52600K .......... .......... .......... .......... .......... 20% 27,7M 11s
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 52750K .......... .......... .......... .......... .......... 20% 28,7M 11s
 52800K .......... .......... .......... .......... .......... 20% 45,9M 11s
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 53000K .......... .......... .......... .......... .......... 20% 31,2M 11s
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 53100K .......... .......... .......... .......... .......... 20% 21,7M 11s
 53150K .......... .......... .......... .......... .......... 20% 36,3M 11s
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 53250K .......... .......... .......... .......... .......... 20% 31,8M 11s
 53300K .......... .......... .......... .......... .......... 20% 17,6M 11s
 53350K .......... .......... .......... .......... .......... 20% 32,8M 11s
 53400K .......... .......... .......... .......... .......... 20% 30,4M 11s
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 53500K .......... .......... .......... .......... .......... 20% 8,45M 11s
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 54000K .......... .......... .......... .......... .......... 21%  838K 11s
 54050K .......... .......... .......... .......... .......... 21% 92,8M 11s
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 55050K .......... .......... .......... .......... .......... 21% 33,1M 11s
 55100K .......... .......... .......... .......... .......... 21% 29,1M 11s
 55150K .......... .......... .......... .......... .......... 21% 21,7M 11s
 55200K .......... .......... .......... .......... .......... 21% 49,8M 11s
 55250K .......... .......... .......... .......... .......... 21% 37,6M 11s
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 56000K .......... .......... .......... .......... .......... 21% 98,9M 11s
 56050K .......... .......... .......... .......... .......... 21% 65,9M 11s
 56100K .......... .......... .......... .......... .......... 22% 22,2M 11s
 56150K .......... .......... .......... .......... .......... 22% 41,2M 11s
 56200K .......... .......... .......... .......... .......... 22% 36,4M 10s
 56250K .......... .......... .......... .......... .......... 22% 40,7M 10s
 56300K .......... .......... .......... .......... .......... 22% 37,2M 10s
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 72150K .......... .......... .......... .......... .......... 28% 27,2M 9s
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 85350K .......... .......... .......... .......... .......... 33%  157M 8s
 85400K .......... .......... .......... .......... .......... 33%  954G 8s
 85450K .......... .......... .......... .......... .......... 33%  134M 8s
 85500K .......... .......... .......... .......... .......... 33%  113M 8s
 85550K .......... .......... .......... .......... .......... 33% 38,9M 8s
 85600K .......... .......... .......... .......... .......... 33%  150M 8s
 85650K .......... .......... .......... .......... .......... 33%  103M 8s
 85700K .......... .......... .......... .......... .......... 33%  954G 8s
 85750K .......... .......... .......... .......... .......... 33% 75,6M 8s
 85800K .......... .......... .......... .......... .......... 33%  127M 8s
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 85900K .......... .......... .......... .......... .......... 33%  954G 8s
 85950K .......... .......... .......... .......... .......... 33%  106M 8s
 86000K .......... .......... .......... .......... .......... 33% 76,1M 8s
 86050K .......... .......... .......... .......... .......... 33% 59,4M 8s
 86100K .......... .......... .......... .......... .......... 33% 76,1M 8s
 86150K .......... .......... .......... .......... .......... 33%  954G 8s
 86200K .......... .......... .......... .......... .......... 33% 63,5M 8s
 86250K .......... .......... .......... .......... .......... 33% 82,3M 8s
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 86350K .......... .......... .......... .......... .......... 33%  954G 8s
 86400K .......... .......... .......... .......... .......... 33%  114M 8s
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 86500K .......... .......... .......... .......... .......... 33% 69,4M 8s
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 86700K .......... .......... .......... .......... .......... 33% 85,3M 8s
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 86800K .......... .......... .......... .......... .......... 34% 21,7M 8s
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 86900K .......... .......... .......... .......... .......... 34% 27,6M 8s
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 87000K .......... .......... .......... .......... .......... 34% 46,9M 8s
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 87100K .......... .......... .......... .......... .......... 34% 36,3M 8s
 87150K .......... .......... .......... .......... .......... 34% 34,3M 8s
 87200K .......... .......... .......... .......... .......... 34% 9,15M 8s
 87250K .......... .......... .......... .......... .......... 34%  125M 8s
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 88100K .......... .......... .......... .......... .......... 34% 37,7M 8s
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 88200K .......... .......... .......... .......... .......... 34% 27,5M 8s
 88250K .......... .......... .......... .......... .......... 34% 32,5M 8s
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 89150K .......... .......... .......... .......... .......... 34% 97,5M 8s
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 89250K .......... .......... .......... .......... .......... 34% 26,7M 8s
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 90900K .......... .......... .......... .......... .......... 35% 98,4M 8s
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 91100K .......... .......... .......... .......... .......... 35% 19,9M 8s
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 91900K .......... .......... .......... .......... .......... 36% 85,8M 8s
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 92150K .......... .......... .......... .......... .......... 36% 49,8M 8s
 92200K .......... .......... .......... .......... .......... 36%  201M 8s
 92250K .......... .......... .......... .......... .......... 36%  954G 8s
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 92750K .......... .......... .......... .......... .......... 36%  273M 8s
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 93000K .......... .......... .......... .......... .......... 36%  240M 8s
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 93150K .......... .......... .......... .......... .......... 36%  954G 8s
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 93250K .......... .......... .......... .......... .......... 36% 80,7M 8s
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 94250K .......... .......... .......... .......... .......... 36% 41,2M 8s
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 95250K .......... .......... .......... .......... .......... 37% 22,7M 8s
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 96950K .......... .......... .......... .......... .......... 38% 61,8M 8s
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 97950K .......... .......... .......... .......... .......... 38% 69,8M 7s
 98000K .......... .......... .......... .......... .......... 38%  134M 7s
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 98250K .......... .......... .......... .......... .......... 38% 39,4M 7s
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 98800K .......... .......... .......... .......... .......... 38% 81,4M 7s
 98850K .......... .......... .......... .......... .......... 38%  148M 7s
 98900K .......... .......... .......... .......... .......... 38% 1,12M 7s
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 99000K .......... .......... .......... .......... .......... 38% 25,7M 7s
 99050K .......... .......... .......... .......... .......... 38%  954G 7s
 99100K .......... .......... .......... .......... .......... 38%  122M 7s
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 99200K .......... .......... .......... .......... .......... 38% 7,69M 7s
 99250K .......... .......... .......... .......... .......... 38% 40,8M 7s
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 99550K .......... .......... .......... .......... .......... 39%  954G 7s
 99600K .......... .......... .......... .......... .......... 39%  163M 7s
 99650K .......... .......... .......... .......... .......... 39%  371M 7s
 99700K .......... .......... .......... .......... .......... 39%  238M 7s
 99750K .......... .......... .......... .......... .......... 39%  360M 7s
 99800K .......... .......... .......... .......... .......... 39%  954G 7s
 99850K .......... .......... .......... .......... .......... 39%  285M 7s
 99900K .......... .......... .......... .......... .......... 39%  391M 7s
 99950K .......... .......... .......... .......... .......... 39%  391M 7s
100000K .......... .......... .......... .......... .......... 39%  954G 7s
100050K .......... .......... .......... .......... .......... 39%  377M 7s
100100K .......... .......... .......... .......... .......... 39%  229M 7s
100150K .......... .......... .......... .......... .......... 39%  394M 7s
100200K .......... .......... .......... .......... .......... 39%  203M 7s
100250K .......... .......... .......... .......... .......... 39%  954G 7s
100300K .......... .......... .......... .......... .......... 39%  340M 7s
100350K .......... .......... .......... .......... .......... 39%  235M 7s
100400K .......... .......... .......... .......... .......... 39% 1,31M 7s
100450K .......... .......... .......... .......... .......... 39%  273M 7s
100500K .......... .......... .......... .......... .......... 39% 35,7M 7s
100550K .......... .......... .......... .......... .......... 39%  236M 7s
100600K .......... .......... .......... .......... .......... 39%  294M 7s
100650K .......... .......... .......... .......... .......... 39%  297M 7s
100700K .......... .......... .......... .......... .......... 39%  954G 7s
100750K .......... .......... .......... .......... .......... 39%  336M 7s
100800K .......... .......... .......... .......... .......... 39% 1,99M 7s
100850K .......... .......... .......... .......... .......... 39% 97,2M 7s
100900K .......... .......... .......... .......... .......... 39%  240M 7s
100950K .......... .......... .......... .......... .......... 39%  954G 7s
101000K .......... .......... .......... .......... .......... 39%  267M 7s
101050K .......... .......... .......... .......... .......... 39%  278M 7s
101100K .......... .......... .......... .......... .......... 39%  270M 7s
101150K .......... .......... .......... .......... .......... 39%  954G 7s
101200K .......... .......... .......... .......... .......... 39%  148M 7s
101250K .......... .......... .......... .......... .......... 39%  256M 7s
101300K .......... .......... .......... .......... .......... 39%  292M 7s
101350K .......... .......... .......... .......... .......... 39%  198M 7s
101400K .......... .......... .......... .......... .......... 39%  954G 7s
101450K .......... .......... .......... .......... .......... 39%  260M 7s
101500K .......... .......... .......... .......... .......... 39% 75,7M 7s
101550K .......... .......... .......... .......... .......... 39% 59,0M 7s
101600K .......... .......... .......... .......... .......... 39% 61,3M 7s
101650K .......... .......... .......... .......... .......... 39%  954G 7s
101700K .......... .......... .......... .......... .......... 39%  103M 7s
101750K .......... .......... .......... .......... .......... 39%  173M 7s
101800K .......... .......... .......... .......... .......... 39% 58,8M 7s
101850K .......... .......... .......... .......... .......... 39%  954G 7s
101900K .......... .......... .......... .......... .......... 39% 61,6M 7s
101950K .......... .......... .......... .......... .......... 39%  291M 7s
102000K .......... .......... .......... .......... .......... 39% 89,9M 7s
102050K .......... .......... .......... .......... .......... 40% 81,5M 7s
102100K .......... .......... .......... .......... .......... 40%  954G 7s
102150K .......... .......... .......... .......... .......... 40%  141M 7s
102200K .......... .......... .......... .......... .......... 40%  337M 7s
102250K .......... .......... .......... .......... .......... 40%  380M 7s
102300K .......... .......... .......... .......... .......... 40%  954G 7s
102350K .......... .......... .......... .......... .......... 40%  235M 7s
102400K .......... .......... .......... .......... .......... 40% 97,2M 7s
102450K .......... .......... .......... .......... .......... 40% 71,9M 7s
102500K .......... .......... .......... .......... .......... 40% 82,8M 7s
102550K .......... .......... .......... .......... .......... 40%  954G 7s
102600K .......... .......... .......... .......... .......... 40% 38,5M 7s
102650K .......... .......... .......... .......... .......... 40%  193M 7s
102700K .......... .......... .......... .......... .......... 40%  350M 7s
102750K .......... .......... .......... .......... .......... 40% 10,4M 7s
102800K .......... .......... .......... .......... .......... 40% 33,3M 7s
102850K .......... .......... .......... .......... .......... 40% 48,1M 7s
102900K .......... .......... .......... .......... .......... 40% 2,79M 7s
102950K .......... .......... .......... .......... .......... 40% 69,5M 7s
103000K .......... .......... .......... .......... .......... 40% 91,0M 7s
103050K .......... .......... .......... .......... .......... 40% 72,8M 7s
103100K .......... .......... .......... .......... .......... 40% 71,9M 7s
103150K .......... .......... .......... .......... .......... 40%  179M 7s
103200K .......... .......... .......... .......... .......... 40% 60,9M 7s
103250K .......... .......... .......... .......... .......... 40% 60,0M 7s
103300K .......... .......... .......... .......... .......... 40% 79,1M 7s
103350K .......... .......... .......... .......... .......... 40%  105M 7s
103400K .......... .......... .......... .......... .......... 40% 78,5M 7s
103450K .......... .......... .......... .......... .......... 40% 16,7M 7s
103500K .......... .......... .......... .......... .......... 40% 43,2M 7s
103550K .......... .......... .......... .......... .......... 40% 22,0M 7s
103600K .......... .......... .......... .......... .......... 40% 40,8M 7s
103650K .......... .......... .......... .......... .......... 40% 29,5M 7s
103700K .......... .......... .......... .......... .......... 40% 33,2M 7s
103750K .......... .......... .......... .......... .......... 40% 49,8M 7s
103800K .......... .......... .......... .......... .......... 40% 34,0M 7s
103850K .......... .......... .......... .......... .......... 40% 26,8M 7s
103900K .......... .......... .......... .......... .......... 40% 21,1M 7s
103950K .......... .......... .......... .......... .......... 40% 34,6M 7s
104000K .......... .......... .......... .......... .......... 40% 21,8M 7s
104050K .......... .......... .......... .......... .......... 40% 37,9M 7s
104100K .......... .......... .......... .......... .......... 40% 37,7M 7s
104150K .......... .......... .......... .......... .......... 40% 39,0M 7s
104200K .......... .......... .......... .......... .......... 40% 24,7M 7s
104250K .......... .......... .......... .......... .......... 40% 27,9M 7s
104300K .......... .......... .......... .......... .......... 40% 28,3M 7s
104350K .......... .......... .......... .......... .......... 40% 47,1M 7s
104400K .......... .......... .......... .......... .......... 40% 44,2M 7s
104450K .......... .......... .......... .......... .......... 40% 37,3M 7s
104500K .......... .......... .......... .......... .......... 40% 42,1M 7s
104550K .......... .......... .......... .......... .......... 40% 41,0M 7s
104600K .......... .......... .......... .......... .......... 41% 37,3M 7s
104650K .......... .......... .......... .......... .......... 41% 33,3M 7s
104700K .......... .......... .......... .......... .......... 41% 18,8M 7s
104750K .......... .......... .......... .......... .......... 41%  910K 7s
104800K .......... .......... .......... .......... .......... 41% 28,2M 7s
104850K .......... .......... .......... .......... .......... 41% 41,2M 7s
104900K .......... .......... .......... .......... .......... 41% 17,4M 7s
104950K .......... .......... .......... .......... .......... 41% 39,9M 7s
105000K .......... .......... .......... .......... .......... 41% 33,0M 7s
105050K .......... .......... .......... .......... .......... 41% 30,4M 7s
105100K .......... .......... .......... .......... .......... 41%  669K 7s
105150K .......... .......... .......... .......... .......... 41% 36,4M 7s
105200K .......... .......... .......... .......... .......... 41%  901K 7s
105250K .......... .......... .......... .......... .......... 41% 30,8M 7s
105300K .......... .......... .......... .......... .......... 41% 28,1M 7s
105350K .......... .......... .......... .......... .......... 41% 29,5M 7s
105400K .......... .......... .......... .......... .......... 41% 28,9M 7s
105450K .......... .......... .......... .......... .......... 41% 38,0M 7s
105500K .......... .......... .......... .......... .......... 41% 15,2M 7s
105550K .......... .......... .......... .......... .......... 41%  546K 7s
105600K .......... .......... .......... .......... .......... 41% 37,9M 7s
105650K .......... .......... .......... .......... .......... 41% 51,1M 7s
105700K .......... .......... .......... .......... .......... 41%  167M 7s
105750K .......... .......... .......... .......... .......... 41%  232M 7s
105800K .......... .......... .......... .......... .......... 41%  954G 7s
105850K .......... .......... .......... .......... .......... 41% 71,9M 7s
105900K .......... .......... .......... .......... .......... 41%  249M 7s
105950K .......... .......... .......... .......... .......... 41%  325M 7s
106000K .......... .......... .......... .......... .......... 41%  162M 7s
106050K .......... .......... .......... .......... .......... 41%  954G 7s
106100K .......... .......... .......... .......... .......... 41%  136M 7s
106150K .......... .......... .......... .......... .......... 41%  313M 7s
106200K .......... .......... .......... .......... .......... 41% 15,5M 7s
106250K .......... .......... .......... .......... .......... 41% 42,1M 7s
106300K .......... .......... .......... .......... .......... 41% 31,0M 7s
106350K .......... .......... .......... .......... .......... 41% 33,2M 7s
106400K .......... .......... .......... .......... .......... 41% 17,1M 7s
106450K .......... .......... .......... .......... .......... 41% 29,6M 7s
106500K .......... .......... .......... .......... .......... 41% 26,9M 7s
106550K .......... .......... .......... .......... .......... 41%  954G 7s
106600K .......... .......... .......... .......... .......... 41%  200M 7s
106650K .......... .......... .......... .......... .......... 41%  239M 7s
106700K .......... .......... .......... .......... .......... 41% 95,9M 7s
106750K .......... .......... .......... .......... .......... 41%  152M 7s
106800K .......... .......... .......... .......... .......... 41%  954G 7s
106850K .......... .......... .......... .......... .......... 41% 84,1M 7s
106900K .......... .......... .......... .......... .......... 41% 60,8M 7s
106950K .......... .......... .......... .......... .......... 41% 57,0M 7s
107000K .......... .......... .......... .......... .......... 41%  954G 7s
107050K .......... .......... .......... .......... .......... 41%  110M 7s
107100K .......... .......... .......... .......... .......... 41% 57,8M 7s
107150K .......... .......... .......... .......... .......... 42% 63,0M 7s
107200K .......... .......... .......... .......... .......... 42%  147M 7s
107250K .......... .......... .......... .......... .......... 42%  954G 7s
107300K .......... .......... .......... .......... .......... 42%  309M 7s
107350K .......... .......... .......... .......... .......... 42%  340M 7s
107400K .......... .......... .......... .......... .......... 42%  356M 7s
107450K .......... .......... .......... .......... .......... 42%  954G 7s
107500K .......... .......... .......... .......... .......... 42%  369M 7s
107550K .......... .......... .......... .......... .......... 42%  262M 7s
107600K .......... .......... .......... .......... .......... 42%  364M 7s
107650K .......... .......... .......... .......... .......... 42%  366M 7s
107700K .......... .......... .......... .......... .......... 42%  954G 7s
107750K .......... .......... .......... .......... .......... 42%  149M 7s
107800K .......... .......... .......... .......... .......... 42%  210M 7s
107850K .......... .......... .......... .......... .......... 42%  377M 7s
107900K .......... .......... .......... .......... .......... 42%  954G 7s
107950K .......... .......... .......... .......... .......... 42%  370M 7s
108000K .......... .......... .......... .......... .......... 42%  367M 7s
108050K .......... .......... .......... .......... .......... 42% 47,5M 7s
108100K .......... .......... .......... .......... .......... 42% 26,9M 7s
108150K .......... .......... .......... .......... .......... 42% 1,23M 7s
108200K .......... .......... .......... .......... .......... 42%  208M 7s
108250K .......... .......... .......... .......... .......... 42%  954G 7s
108300K .......... .......... .......... .......... .......... 42%  229M 7s
108350K .......... .......... .......... .......... .......... 42% 10,2M 7s
108400K .......... .......... .......... .......... .......... 42%  215M 7s
108450K .......... .......... .......... .......... .......... 42% 33,2M 7s
108500K .......... .......... .......... .......... .......... 42% 20,1M 7s
108550K .......... .......... .......... .......... .......... 42%  480M 7s
108600K .......... .......... .......... .......... .......... 42%  368M 7s
108650K .......... .......... .......... .......... .......... 42%  304M 7s
108700K .......... .......... .......... .......... .......... 42% 93,7M 7s
108750K .......... .......... .......... .......... .......... 42% 5,15M 7s
108800K .......... .......... .......... .......... .......... 42% 14,3M 7s
108850K .......... .......... .......... .......... .......... 42% 38,8M 7s
108900K .......... .......... .......... .......... .......... 42% 85,9M 7s
108950K .......... .......... .......... .......... .......... 42%  954G 7s
109000K .......... .......... .......... .......... .......... 42%  236M 7s
109050K .......... .......... .......... .......... .......... 42%  311M 7s
109100K .......... .......... .......... .......... .......... 42% 2,57M 7s
109150K .......... .......... .......... .......... .......... 42% 19,1M 7s
109200K .......... .......... .......... .......... .......... 42%  954G 7s
109250K .......... .......... .......... .......... .......... 42%  261M 7s
109300K .......... .......... .......... .......... .......... 42%  284M 7s
109350K .......... .......... .......... .......... .......... 42%  332M 7s
109400K .......... .......... .......... .......... .......... 42%  954G 7s
109450K .......... .......... .......... .......... .......... 42%  180M 7s
109500K .......... .......... .......... .......... .......... 42%  321M 7s
109550K .......... .......... .......... .......... .......... 42%  211M 7s
109600K .......... .......... .......... .......... .......... 42%  294M 7s
109650K .......... .......... .......... .......... .......... 42%  954G 7s
109700K .......... .......... .......... .......... .......... 43%  180M 7s
109750K .......... .......... .......... .......... .......... 43%  119M 7s
109800K .......... .......... .......... .......... .......... 43%  144M 7s
109850K .......... .......... .......... .......... .......... 43%  954G 7s
109900K .......... .......... .......... .......... .......... 43%  197M 7s
109950K .......... .......... .......... .......... .......... 43%  215M 7s
110000K .......... .......... .......... .......... .......... 43% 90,7M 7s
110050K .......... .......... .......... .......... .......... 43%  181M 7s
110100K .......... .......... .......... .......... .......... 43%  954G 7s
110150K .......... .......... .......... .......... .......... 43%  167M 7s
110200K .......... .......... .......... .......... .......... 43% 84,1M 7s
110250K .......... .......... .......... .......... .......... 43%  129M 7s
110300K .......... .......... .......... .......... .......... 43%  235M 7s
110350K .......... .......... .......... .......... .......... 43%  329M 7s
110400K .......... .......... .......... .......... .......... 43%  141M 7s
110450K .......... .......... .......... .......... .......... 43% 63,0M 7s
110500K .......... .......... .......... .......... .......... 43%  155M 7s
110550K .......... .......... .......... .......... .......... 43% 28,3M 7s
110600K .......... .......... .......... .......... .......... 43% 86,2M 7s
110650K .......... .......... .......... .......... .......... 43%  140M 7s
110700K .......... .......... .......... .......... .......... 43% 47,1M 7s
110750K .......... .......... .......... .......... .......... 43% 31,2M 7s
110800K .......... .......... .......... .......... .......... 43% 17,7M 7s
110850K .......... .......... .......... .......... .......... 43% 29,3M 7s
110900K .......... .......... .......... .......... .......... 43% 43,2M 7s
110950K .......... .......... .......... .......... .......... 43% 30,9M 7s
111000K .......... .......... .......... .......... .......... 43% 18,1M 7s
111050K .......... .......... .......... .......... .......... 43% 68,3M 7s
111100K .......... .......... .......... .......... .......... 43% 5,50M 7s
111150K .......... .......... .......... .......... .......... 43%  184M 7s
111200K .......... .......... .......... .......... .......... 43%  143M 7s
111250K .......... .......... .......... .......... .......... 43%  175M 7s
111300K .......... .......... .......... .......... .......... 43% 81,1M 7s
111350K .......... .......... .......... .......... .......... 43% 81,6M 7s
111400K .......... .......... .......... .......... .......... 43% 32,1M 7s
111450K .......... .......... .......... .......... .......... 43% 13,9M 7s
111500K .......... .......... .......... .......... .......... 43% 98,3M 7s
111550K .......... .......... .......... .......... .......... 43% 24,3M 7s
111600K .......... .......... .......... .......... .......... 43% 77,3M 7s
111650K .......... .......... .......... .......... .......... 43% 9,93M 7s
111700K .......... .......... .......... .......... .......... 43% 87,3M 7s
111750K .......... .......... .......... .......... .......... 43%  110M 7s
111800K .......... .......... .......... .......... .......... 43% 4,73M 7s
111850K .......... .......... .......... .......... .......... 43% 84,4M 7s
111900K .......... .......... .......... .......... .......... 43%  121M 7s
111950K .......... .......... .......... .......... .......... 43% 86,6M 7s
112000K .......... .......... .......... .......... .......... 43% 69,0M 7s
112050K .......... .......... .......... .......... .......... 43% 57,3M 7s
112100K .......... .......... .......... .......... .......... 43% 72,9M 7s
112150K .......... .......... .......... .......... .......... 43% 41,5M 7s
112200K .......... .......... .......... .......... .......... 43% 43,7M 7s
112250K .......... .......... .......... .......... .......... 44% 28,7M 7s
112300K .......... .......... .......... .......... .......... 44% 39,7M 7s
112350K .......... .......... .......... .......... .......... 44% 30,1M 7s
112400K .......... .......... .......... .......... .......... 44% 38,0M 7s
112450K .......... .......... .......... .......... .......... 44% 18,7M 7s
112500K .......... .......... .......... .......... .......... 44% 4,49M 7s
112550K .......... .......... .......... .......... .......... 44%  118M 7s
112600K .......... .......... .......... .......... .......... 44% 65,4M 7s
112650K .......... .......... .......... .......... .......... 44%  256M 7s
112700K .......... .......... .......... .......... .......... 44% 11,3M 7s
112750K .......... .......... .......... .......... .......... 44% 73,8M 7s
112800K .......... .......... .......... .......... .......... 44% 7,69M 7s
112850K .......... .......... .......... .......... .......... 44%  131M 7s
112900K .......... .......... .......... .......... .......... 44%  118M 7s
112950K .......... .......... .......... .......... .......... 44%  111M 7s
113000K .......... .......... .......... .......... .......... 44% 66,7M 7s
113050K .......... .......... .......... .......... .......... 44% 40,0M 7s
113100K .......... .......... .......... .......... .......... 44% 33,5M 7s
113150K .......... .......... .......... .......... .......... 44% 27,8M 7s
113200K .......... .......... .......... .......... .......... 44% 10,4M 7s
113250K .......... .......... .......... .......... .......... 44% 57,5M 7s
113300K .......... .......... .......... .......... .......... 44% 30,1M 7s
113350K .......... .......... .......... .......... .......... 44% 34,5M 7s
113400K .......... .......... .......... .......... .......... 44% 27,2M 7s
113450K .......... .......... .......... .......... .......... 44% 9,53M 7s
113500K .......... .......... .......... .......... .......... 44%  108M 7s
113550K .......... .......... .......... .......... .......... 44% 39,3M 7s
113600K .......... .......... .......... .......... .......... 44%  179M 7s
113650K .......... .......... .......... .......... .......... 44% 1,22M 7s
113700K .......... .......... .......... .......... .......... 44%  338M 7s
113750K .......... .......... .......... .......... .......... 44%  954G 7s
113800K .......... .......... .......... .......... .......... 44% 9,20M 7s
113850K .......... .......... .......... .......... .......... 44%  216M 7s
113900K .......... .......... .......... .......... .......... 44%  192M 7s
113950K .......... .......... .......... .......... .......... 44%  954G 7s
114000K .......... .......... .......... .......... .......... 44%  188M 7s
114050K .......... .......... .......... .......... .......... 44%  157M 7s
114100K .......... .......... .......... .......... .......... 44%  293M 7s
114150K .......... .......... .......... .......... .......... 44% 8,96M 7s
114200K .......... .......... .......... .......... .......... 44%  954G 7s
114250K .......... .......... .......... .......... .......... 44%  161M 7s
114300K .......... .......... .......... .......... .......... 44%  308M 7s
114350K .......... .......... .......... .......... .......... 44%  195M 7s
114400K .......... .......... .......... .......... .......... 44%  339M 7s
114450K .......... .......... .......... .......... .......... 44%  954G 7s
114500K .......... .......... .......... .......... .......... 44%  331M 7s
114550K .......... .......... .......... .......... .......... 44%  327M 7s
114600K .......... .......... .......... .......... .......... 44%  199M 7s
114650K .......... .......... .......... .......... .......... 44%  954G 7s
114700K .......... .......... .......... .......... .......... 44%  130M 7s
114750K .......... .......... .......... .......... .......... 44%  308M 7s
114800K .......... .......... .......... .......... .......... 45% 98,0M 7s
114850K .......... .......... .......... .......... .......... 45%  127M 7s
114900K .......... .......... .......... .......... .......... 45%  954G 7s
114950K .......... .......... .......... .......... .......... 45% 48,3M 7s
115000K .......... .......... .......... .......... .......... 45% 14,1M 7s
115050K .......... .......... .......... .......... .......... 45% 22,6M 7s
115100K .......... .......... .......... .......... .......... 45%  125M 7s
115150K .......... .......... .......... .......... .......... 45% 39,2M 7s
115200K .......... .......... .......... .......... .......... 45% 13,3M 7s
115250K .......... .......... .......... .......... .......... 45% 88,3M 7s
115300K .......... .......... .......... .......... .......... 45% 7,93M 7s
115350K .......... .......... .......... .......... .......... 45% 66,1M 7s
115400K .......... .......... .......... .......... .......... 45% 76,1M 7s
115450K .......... .......... .......... .......... .......... 45%  137M 7s
115500K .......... .......... .......... .......... .......... 45% 96,7M 7s
115550K .......... .......... .......... .......... .......... 45% 48,0M 7s
115600K .......... .......... .......... .......... .......... 45% 4,92M 7s
115650K .......... .......... .......... .......... .......... 45% 78,9M 7s
115700K .......... .......... .......... .......... .......... 45%  115M 7s
115750K .......... .......... .......... .......... .......... 45% 73,2M 7s
115800K .......... .......... .......... .......... .......... 45% 88,0M 7s
115850K .......... .......... .......... .......... .......... 45% 55,8M 7s
115900K .......... .......... .......... .......... .......... 45% 91,5M 7s
115950K .......... .......... .......... .......... .......... 45% 46,4M 7s
116000K .......... .......... .......... .......... .......... 45% 84,6M 7s
116050K .......... .......... .......... .......... .......... 45% 52,6M 7s
116100K .......... .......... .......... .......... .......... 45% 21,4M 7s
116150K .......... .......... .......... .......... .......... 45% 36,3M 7s
116200K .......... .......... .......... .......... .......... 45% 8,71M 7s
116250K .......... .......... .......... .......... .......... 45%  126M 7s
116300K .......... .......... .......... .......... .......... 45% 56,5M 7s
116350K .......... .......... .......... .......... .......... 45%  212M 7s
116400K .......... .......... .......... .......... .......... 45% 27,8M 7s
116450K .......... .......... .......... .......... .......... 45% 33,4M 7s
116500K .......... .......... .......... .......... .......... 45% 6,47M 7s
116550K .......... .......... .......... .......... .......... 45% 92,3M 7s
116600K .......... .......... .......... .......... .......... 45% 75,1M 7s
116650K .......... .......... .......... .......... .......... 45% 20,6M 7s
116700K .......... .......... .......... .......... .......... 45% 74,2M 7s
116750K .......... .......... .......... .......... .......... 45%  115M 7s
116800K .......... .......... .......... .......... .......... 45% 21,6M 7s
116850K .......... .......... .......... .......... .......... 45% 66,2M 7s
116900K .......... .......... .......... .......... .......... 45% 39,7M 7s
116950K .......... .......... .......... .......... .......... 45% 51,1M 7s
117000K .......... .......... .......... .......... .......... 45% 28,3M 7s
117050K .......... .......... .......... .......... .......... 45% 12,3M 7s
117100K .......... .......... .......... .......... .......... 45% 37,8M 7s
117150K .......... .......... .......... .......... .......... 45% 34,3M 7s
117200K .......... .......... .......... .......... .......... 45% 18,3M 7s
117250K .......... .......... .......... .......... .......... 45%  104M 7s
117300K .......... .......... .......... .......... .......... 45% 23,0M 7s
117350K .......... .......... .......... .......... .......... 46%  126M 7s
117400K .......... .......... .......... .......... .......... 46% 30,0M 7s
117450K .......... .......... .......... .......... .......... 46% 12,7M 7s
117500K .......... .......... .......... .......... .......... 46% 21,1M 7s
117550K .......... .......... .......... .......... .......... 46% 37,8M 7s
117600K .......... .......... .......... .......... .......... 46% 28,1M 7s
117650K .......... .......... .......... .......... .......... 46% 20,7M 7s
117700K .......... .......... .......... .......... .......... 46%  115M 7s
117750K .......... .......... .......... .......... .......... 46% 1,27M 7s
117800K .......... .......... .......... .......... .......... 46%  990K 7s
117850K .......... .......... .......... .......... .......... 46% 8,80M 7s
117900K .......... .......... .......... .......... .......... 46%  239M 7s
117950K .......... .......... .......... .......... .......... 46%  131M 7s
118000K .......... .......... .......... .......... .......... 46% 34,8M 7s
118050K .......... .......... .......... .......... .......... 46%  954G 7s
118100K .......... .......... .......... .......... .......... 46%  166M 7s
118150K .......... .......... .......... .......... .......... 46%  219M 7s
118200K .......... .......... .......... .......... .......... 46%  230M 7s
118250K .......... .......... .......... .......... .......... 46%  252M 7s
118300K .......... .......... .......... .......... .......... 46%  954G 7s
118350K .......... .......... .......... .......... .......... 46%  264M 7s
118400K .......... .......... .......... .......... .......... 46%  268M 7s
118450K .......... .......... .......... .......... .......... 46%  258M 7s
118500K .......... .......... .......... .......... .......... 46%  954G 7s
118550K .......... .......... .......... .......... .......... 46%  218M 7s
118600K .......... .......... .......... .......... .......... 46%  313M 7s
118650K .......... .......... .......... .......... .......... 46%  119M 7s
118700K .......... .......... .......... .......... .......... 46%  141M 7s
118750K .......... .......... .......... .......... .......... 46%  954G 7s
118800K .......... .......... .......... .......... .......... 46%  119M 7s
118850K .......... .......... .......... .......... .......... 46%  228M 7s
118900K .......... .......... .......... .......... .......... 46%  252M 7s
118950K .......... .......... .......... .......... .......... 46%  220M 7s
119000K .......... .......... .......... .......... .......... 46%  954G 7s
119050K .......... .......... .......... .......... .......... 46%  156M 7s
119100K .......... .......... .......... .......... .......... 46%  342M 6s
119150K .......... .......... .......... .......... .......... 46%  135M 6s
119200K .......... .......... .......... .......... .......... 46%  954G 6s
119250K .......... .......... .......... .......... .......... 46%  202M 6s
119300K .......... .......... .......... .......... .......... 46%  246M 6s
119350K .......... .......... .......... .......... .......... 46%  272M 6s
119400K .......... .......... .......... .......... .......... 46%  148M 6s
119450K .......... .......... .......... .......... .......... 46%  954G 6s
119500K .......... .......... .......... .......... .......... 46%  268M 6s
119550K .......... .......... .......... .......... .......... 46%  254M 6s
119600K .......... .......... .......... .......... .......... 46%  252M 6s
119650K .......... .......... .......... .......... .......... 46%  954G 6s
119700K .......... .......... .......... .......... .......... 46%  237M 6s
119750K .......... .......... .......... .......... .......... 46%  245M 6s
119800K .......... .......... .......... .......... .......... 46% 89,0M 6s
119850K .......... .......... .......... .......... .......... 46%  173M 6s
119900K .......... .......... .......... .......... .......... 47%  954G 6s
119950K .......... .......... .......... .......... .......... 47% 60,1M 6s
120000K .......... .......... .......... .......... .......... 47% 64,8M 6s
120050K .......... .......... .......... .......... .......... 47% 86,3M 6s
120100K .......... .......... .......... .......... .......... 47%  954G 6s
120150K .......... .......... .......... .......... .......... 47%  102M 6s
120200K .......... .......... .......... .......... .......... 47%  124M 6s
120250K .......... .......... .......... .......... .......... 47%  256M 6s
120300K .......... .......... .......... .......... .......... 47%  175M 6s
120350K .......... .......... .......... .......... .......... 47%  954G 6s
120400K .......... .......... .......... .......... .......... 47%  325M 6s
120450K .......... .......... .......... .......... .......... 47% 9,74M 6s
120500K .......... .......... .......... .......... .......... 47% 38,1M 6s
120550K .......... .......... .......... .......... .......... 47% 30,9M 6s
120600K .......... .......... .......... .......... .......... 47% 31,8M 6s
120650K .......... .......... .......... .......... .......... 47% 34,4M 6s
120700K .......... .......... .......... .......... .......... 47% 19,1M 6s
120750K .......... .......... .......... .......... .......... 47% 79,7M 6s
120800K .......... .......... .......... .......... .......... 47% 12,8M 6s
120850K .......... .......... .......... .......... .......... 47%  132M 6s
120900K .......... .......... .......... .......... .......... 47% 24,6M 6s
120950K .......... .......... .......... .......... .......... 47% 39,0M 6s
121000K .......... .......... .......... .......... .......... 47% 30,2M 6s
121050K .......... .......... .......... .......... .......... 47% 15,3M 6s
121100K .......... .......... .......... .......... .......... 47% 40,2M 6s
121150K .......... .......... .......... .......... .......... 47% 30,3M 6s
121200K .......... .......... .......... .......... .......... 47% 34,0M 6s
121250K .......... .......... .......... .......... .......... 47% 10,8M 6s
121300K .......... .......... .......... .......... .......... 47% 15,4M 6s
121350K .......... .......... .......... .......... .......... 47% 32,2M 6s
121400K .......... .......... .......... .......... .......... 47% 24,9M 6s
121450K .......... .......... .......... .......... .......... 47% 58,3M 6s
121500K .......... .......... .......... .......... .......... 47% 38,1M 6s
121550K .......... .......... .......... .......... .......... 47% 36,6M 6s
121600K .......... .......... .......... .......... .......... 47% 1,46M 6s
121650K .......... .......... .......... .......... .......... 47% 18,0M 6s
121700K .......... .......... .......... .......... .......... 47%  954G 6s
121750K .......... .......... .......... .......... .......... 47% 11,7M 6s
121800K .......... .......... .......... .......... .......... 47% 21,6M 6s
121850K .......... .......... .......... .......... .......... 47%  110M 6s
121900K .......... .......... .......... .......... .......... 47% 93,0M 6s
121950K .......... .......... .......... .......... .......... 47%  172M 6s
122000K .......... .......... .......... .......... .......... 47%  377M 6s
122050K .......... .......... .......... .......... .......... 47%  954G 6s
122100K .......... .......... .......... .......... .......... 47%  372M 6s
122150K .......... .......... .......... .......... .......... 47% 5,68M 6s
122200K .......... .......... .......... .......... .......... 47% 29,3M 6s
122250K .......... .......... .......... .......... .......... 47% 43,8M 6s
122300K .......... .......... .......... .......... .......... 47% 31,0M 6s
122350K .......... .......... .......... .......... .......... 47% 14,0M 6s
122400K .......... .......... .......... .......... .......... 47%  954G 6s
122450K .......... .......... .......... .......... .......... 48%  273M 6s
122500K .......... .......... .......... .......... .......... 48%  132M 6s
122550K .......... .......... .......... .......... .......... 48%  317M 6s
122600K .......... .......... .......... .......... .......... 48%  382M 6s
122650K .......... .......... .......... .......... .......... 48%  954G 6s
122700K .......... .......... .......... .......... .......... 48%  388M 6s
122750K .......... .......... .......... .......... .......... 48%  399M 6s
122800K .......... .......... .......... .......... .......... 48%  132M 6s
122850K .......... .......... .......... .......... .......... 48%  954G 6s
122900K .......... .......... .......... .......... .......... 48%  125M 6s
122950K .......... .......... .......... .......... .......... 48%  372M 6s
123000K .......... .......... .......... .......... .......... 48% 70,5M 6s
123050K .......... .......... .......... .......... .......... 48% 44,2M 6s
123100K .......... .......... .......... .......... .......... 48%  954G 6s
123150K .......... .......... .......... .......... .......... 48% 68,3M 6s
123200K .......... .......... .......... .......... .......... 48% 92,2M 6s
123250K .......... .......... .......... .......... .......... 48%  264M 6s
123300K .......... .......... .......... .......... .......... 48% 93,2M 6s
123350K .......... .......... .......... .......... .......... 48% 24,4M 6s
123400K .......... .......... .......... .......... .......... 48% 19,4M 6s
123450K .......... .......... .......... .......... .......... 48% 15,5M 6s
123500K .......... .......... .......... .......... .......... 48% 7,12M 6s
123550K .......... .......... .......... .......... .......... 48% 17,2M 6s
123600K .......... .......... .......... .......... .......... 48% 38,2M 6s
123650K .......... .......... .......... .......... .......... 48% 37,7M 6s
123700K .......... .......... .......... .......... .......... 48% 38,4M 6s
123750K .......... .......... .......... .......... .......... 48% 36,7M 6s
123800K .......... .......... .......... .......... .......... 48% 33,7M 6s
123850K .......... .......... .......... .......... .......... 48% 41,4M 6s
123900K .......... .......... .......... .......... .......... 48% 36,3M 6s
123950K .......... .......... .......... .......... .......... 48% 16,8M 6s
124000K .......... .......... .......... .......... .......... 48% 33,6M 6s
124050K .......... .......... .......... .......... .......... 48% 44,6M 6s
124100K .......... .......... .......... .......... .......... 48% 26,1M 6s
124150K .......... .......... .......... .......... .......... 48% 32,9M 6s
124200K .......... .......... .......... .......... .......... 48% 35,7M 6s
124250K .......... .......... .......... .......... .......... 48% 34,8M 6s
124300K .......... .......... .......... .......... .......... 48% 45,1M 6s
124350K .......... .......... .......... .......... .......... 48% 18,5M 6s
124400K .......... .......... .......... .......... .......... 48% 32,3M 6s
124450K .......... .......... .......... .......... .......... 48% 21,0M 6s
124500K .......... .......... .......... .......... .......... 48% 38,9M 6s
124550K .......... .......... .......... .......... .......... 48% 27,9M 6s
124600K .......... .......... .......... .......... .......... 48% 37,7M 6s
124650K .......... .......... .......... .......... .......... 48% 16,1M 6s
124700K .......... .......... .......... .......... .......... 48% 38,7M 6s
124750K .......... .......... .......... .......... .......... 48% 40,3M 6s
124800K .......... .......... .......... .......... .......... 48% 21,7M 6s
124850K .......... .......... .......... .......... .......... 48% 34,9M 6s
124900K .......... .......... .......... .......... .......... 48% 20,2M 6s
124950K .......... .......... .......... .......... .......... 48% 35,1M 6s
125000K .......... .......... .......... .......... .......... 49% 29,3M 6s
125050K .......... .......... .......... .......... .......... 49% 36,3M 6s
125100K .......... .......... .......... .......... .......... 49% 36,1M 6s
125150K .......... .......... .......... .......... .......... 49% 37,3M 6s
125200K .......... .......... .......... .......... .......... 49% 29,2M 6s
125250K .......... .......... .......... .......... .......... 49% 17,9M 6s
125300K .......... .......... .......... .......... .......... 49% 46,8M 6s
125350K .......... .......... .......... .......... .......... 49% 23,8M 6s
125400K .......... .......... .......... .......... .......... 49% 45,2M 6s
125450K .......... .......... .......... .......... .......... 49% 25,5M 6s
125500K .......... .......... .......... .......... .......... 49% 39,6M 6s
125550K .......... .......... .......... .......... .......... 49% 30,8M 6s
125600K .......... .......... .......... .......... .......... 49% 21,8M 6s
125650K .......... .......... .......... .......... .......... 49% 21,0M 6s
125700K .......... .......... .......... .......... .......... 49% 21,1M 6s
125750K .......... .......... .......... .......... .......... 49% 10,7M 6s
125800K .......... .......... .......... .......... .......... 49% 36,5M 6s
125850K .......... .......... .......... .......... .......... 49% 23,3M 6s
125900K .......... .......... .......... .......... .......... 49% 50,8M 6s
125950K .......... .......... .......... .......... .......... 49% 11,4M 6s
126000K .......... .......... .......... .......... .......... 49% 74,2M 6s
126050K .......... .......... .......... .......... .......... 49% 24,2M 6s
126100K .......... .......... .......... .......... .......... 49% 53,5M 6s
126150K .......... .......... .......... .......... .......... 49% 35,8M 6s
126200K .......... .......... .......... .......... .......... 49% 29,8M 6s
126250K .......... .......... .......... .......... .......... 49% 34,6M 6s
126300K .......... .......... .......... .......... .......... 49% 30,0M 6s
126350K .......... .......... .......... .......... .......... 49% 16,0M 6s
126400K .......... .......... .......... .......... .......... 49% 37,0M 6s
126450K .......... .......... .......... .......... .......... 49% 30,7M 6s
126500K .......... .......... .......... .......... .......... 49% 50,6M 6s
126550K .......... .......... .......... .......... .......... 49% 9,05M 6s
126600K .......... .......... .......... .......... .......... 49% 34,6M 6s
126650K .......... .......... .......... .......... .......... 49% 38,1M 6s
126700K .......... .......... .......... .......... .......... 49% 29,9M 6s
126750K .......... .......... .......... .......... .......... 49% 17,3M 6s
126800K .......... .......... .......... .......... .......... 49% 33,4M 6s
126850K .......... .......... .......... .......... .......... 49% 35,0M 6s
126900K .......... .......... .......... .......... .......... 49% 29,7M 6s
126950K .......... .......... .......... .......... .......... 49% 28,8M 6s
127000K .......... .......... .......... .......... .......... 49% 15,1M 6s
127050K .......... .......... .......... .......... .......... 49% 22,5M 6s
127100K .......... .......... .......... .......... .......... 49% 68,2M 6s
127150K .......... .......... .......... .......... .......... 49% 6,27M 6s
127200K .......... .......... .......... .......... .......... 49% 61,8M 6s
127250K .......... .......... .......... .......... .......... 49% 15,4M 6s
127300K .......... .......... .......... .......... .......... 49% 36,8M 6s
127350K .......... .......... .......... .......... .......... 49% 34,8M 6s
127400K .......... .......... .......... .......... .......... 49% 4,96M 6s
127450K .......... .......... .......... .......... .......... 49% 69,5M 6s
127500K .......... .......... .......... .......... .......... 49%  982K 6s
127550K .......... .......... .......... .......... .......... 50% 31,8M 6s
127600K .......... .......... .......... .......... .......... 50% 34,3M 6s
127650K .......... .......... .......... .......... .......... 50% 47,6M 6s
127700K .......... .......... .......... .......... .......... 50%  193M 6s
127750K .......... .......... .......... .......... .......... 50%  194M 6s
127800K .......... .......... .......... .......... .......... 50% 28,6M 6s
127850K .......... .......... .......... .......... .......... 50% 46,5M 6s
127900K .......... .......... .......... .......... .......... 50% 92,9M 6s
127950K .......... .......... .......... .......... .......... 50%  376M 6s
128000K .......... .......... .......... .......... .......... 50% 12,0M 6s
128050K .......... .......... .......... .......... .......... 50% 18,9M 6s
128100K .......... .......... .......... .......... .......... 50%  139M 6s
128150K .......... .......... .......... .......... .......... 50%  265M 6s
128200K .......... .......... .......... .......... .......... 50% 13,2M 6s
128250K .......... .......... .......... .......... .......... 50% 26,4M 6s
128300K .......... .......... .......... .......... .......... 50%  954G 6s
128350K .......... .......... .......... .......... .......... 50%  135M 6s
128400K .......... .......... .......... .......... .......... 50%  246M 6s
128450K .......... .......... .......... .......... .......... 50%  269M 6s
128500K .......... .......... .......... .......... .......... 50%  954G 6s
128550K .......... .......... .......... .......... .......... 50%  300M 6s
128600K .......... .......... .......... .......... .......... 50%  186M 6s
128650K .......... .......... .......... .......... .......... 50%  176M 6s
128700K .......... .......... .......... .......... .......... 50%  386M 6s
128750K .......... .......... .......... .......... .......... 50%  954G 6s
128800K .......... .......... .......... .......... .......... 50%  360M 6s
128850K .......... .......... .......... .......... .......... 50%  399M 6s
128900K .......... .......... .......... .......... .......... 50%  226M 6s
128950K .......... .......... .......... .......... .......... 50%  388M 6s
129000K .......... .......... .......... .......... .......... 50%  954G 6s
129050K .......... .......... .......... .......... .......... 50% 1,46M 6s
129100K .......... .......... .......... .......... .......... 50% 24,8M 6s
129150K .......... .......... .......... .......... .......... 50%  314M 6s
129200K .......... .......... .......... .......... .......... 50% 26,6M 6s
129250K .......... .......... .......... .......... .......... 50% 92,3M 6s
129300K .......... .......... .......... .......... .......... 50%  954G 6s
129350K .......... .......... .......... .......... .......... 50%  218M 6s
129400K .......... .......... .......... .......... .......... 50%  169M 6s
129450K .......... .......... .......... .......... .......... 50%  150M 6s
129500K .......... .......... .......... .......... .......... 50%  131M 6s
129550K .......... .......... .......... .......... .......... 50%  954G 6s
129600K .......... .......... .......... .......... .......... 50%  164M 6s
129650K .......... .......... .......... .......... .......... 50%  334M 6s
129700K .......... .......... .......... .......... .......... 50%  391M 6s
129750K .......... .......... .......... .......... .......... 50%  954G 6s
129800K .......... .......... .......... .......... .......... 50%  174M 6s
129850K .......... .......... .......... .......... .......... 50%  315M 6s
129900K .......... .......... .......... .......... .......... 50%  305M 6s
129950K .......... .......... .......... .......... .......... 50%  361M 6s
130000K .......... .......... .......... .......... .......... 50%  954G 6s
130050K .......... .......... .......... .......... .......... 50%  103M 6s
130100K .......... .......... .......... .......... .......... 51%  192M 6s
130150K .......... .......... .......... .......... .......... 51%  133M 6s
130200K .......... .......... .......... .......... .......... 51%  954G 6s
130250K .......... .......... .......... .......... .......... 51% 57,3M 6s
130300K .......... .......... .......... .......... .......... 51% 40,9M 6s
130350K .......... .......... .......... .......... .......... 51% 30,5M 6s
130400K .......... .......... .......... .......... .......... 51% 45,6M 6s
130450K .......... .......... .......... .......... .......... 51% 14,7M 6s
130500K .......... .......... .......... .......... .......... 51% 15,6M 6s
130550K .......... .......... .......... .......... .......... 51% 26,2M 6s
130600K .......... .......... .......... .......... .......... 51% 28,8M 6s
130650K .......... .......... .......... .......... .......... 51% 51,4M 6s
130700K .......... .......... .......... .......... .......... 51% 33,7M 6s
130750K .......... .......... .......... .......... .......... 51% 39,9M 6s
130800K .......... .......... .......... .......... .......... 51% 34,4M 6s
130850K .......... .......... .......... .......... .......... 51% 12,3M 6s
130900K .......... .......... .......... .......... .......... 51% 8,44M 6s
130950K .......... .......... .......... .......... .......... 51%  108M 6s
131000K .......... .......... .......... .......... .......... 51% 76,3M 6s
131050K .......... .......... .......... .......... .......... 51%  112M 6s
131100K .......... .......... .......... .......... .......... 51%  145M 6s
131150K .......... .......... .......... .......... .......... 51% 21,5M 6s
131200K .......... .......... .......... .......... .......... 51%  114M 6s
131250K .......... .......... .......... .......... .......... 51% 38,0M 6s
131300K .......... .......... .......... .......... .......... 51% 18,0M 6s
131350K .......... .......... .......... .......... .......... 51% 16,7M 6s
131400K .......... .......... .......... .......... .......... 51% 36,9M 6s
131450K .......... .......... .......... .......... .......... 51% 37,0M 6s
131500K .......... .......... .......... .......... .......... 51% 38,0M 6s
131550K .......... .......... .......... .......... .......... 51% 22,5M 6s
131600K .......... .......... .......... .......... .......... 51% 37,5M 6s
131650K .......... .......... .......... .......... .......... 51% 40,2M 6s
131700K .......... .......... .......... .......... .......... 51% 17,7M 6s
131750K .......... .......... .......... .......... .......... 51% 32,7M 6s
131800K .......... .......... .......... .......... .......... 51% 27,1M 6s
131850K .......... .......... .......... .......... .......... 51% 29,9M 6s
131900K .......... .......... .......... .......... .......... 51% 36,0M 6s
131950K .......... .......... .......... .......... .......... 51% 30,7M 6s
132000K .......... .......... .......... .......... .......... 51% 34,8M 6s
132050K .......... .......... .......... .......... .......... 51% 31,6M 6s
132100K .......... .......... .......... .......... .......... 51% 37,6M 6s
132150K .......... .......... .......... .......... .......... 51% 18,5M 6s
132200K .......... .......... .......... .......... .......... 51% 29,9M 6s
132250K .......... .......... .......... .......... .......... 51% 30,6M 6s
132300K .......... .......... .......... .......... .......... 51% 36,7M 6s
132350K .......... .......... .......... .......... .......... 51% 34,1M 6s
132400K .......... .......... .......... .......... .......... 51% 16,4M 6s
132450K .......... .......... .......... .......... .......... 51% 37,6M 6s
132500K .......... .......... .......... .......... .......... 51% 26,9M 6s
132550K .......... .......... .......... .......... .......... 51% 16,9M 6s
132600K .......... .......... .......... .......... .......... 51% 29,2M 6s
132650K .......... .......... .......... .......... .......... 52% 35,8M 6s
132700K .......... .......... .......... .......... .......... 52% 34,6M 6s
132750K .......... .......... .......... .......... .......... 52% 39,9M 6s
132800K .......... .......... .......... .......... .......... 52% 1,03M 6s
132850K .......... .......... .......... .......... .......... 52%  239M 6s
132900K .......... .......... .......... .......... .......... 52% 28,9M 6s
132950K .......... .......... .......... .......... .......... 52% 18,4M 6s
133000K .......... .......... .......... .......... .......... 52%  183M 6s
133050K .......... .......... .......... .......... .......... 52% 44,7M 6s
133100K .......... .......... .......... .......... .......... 52% 47,4M 6s
133150K .......... .......... .......... .......... .......... 52%  122M 6s
133200K .......... .......... .......... .......... .......... 52% 8,84M 6s
133250K .......... .......... .......... .......... .......... 52% 64,7M 6s
133300K .......... .......... .......... .......... .......... 52% 21,3M 6s
133350K .......... .......... .......... .......... .......... 52%  260M 6s
133400K .......... .......... .......... .......... .......... 52%  406M 6s
133450K .......... .......... .......... .......... .......... 52% 59,5M 6s
133500K .......... .......... .......... .......... .......... 52%  307M 6s
133550K .......... .......... .......... .......... .......... 52%  386M 6s
133600K .......... .......... .......... .......... .......... 52%  954G 6s
133650K .......... .......... .......... .......... .......... 52%  346M 6s
133700K .......... .......... .......... .......... .......... 52%  195M 6s
133750K .......... .......... .......... .......... .......... 52%  400M 6s
133800K .......... .......... .......... .......... .......... 52%  415M 6s
133850K .......... .......... .......... .......... .......... 52% 3,16M 6s
133900K .......... .......... .......... .......... .......... 52% 91,7M 6s
133950K .......... .......... .......... .......... .......... 52% 29,3M 6s
134000K .......... .......... .......... .......... .......... 52%  954G 6s
134050K .......... .......... .......... .......... .......... 52%  106M 6s
134100K .......... .......... .......... .......... .......... 52%  267M 6s
134150K .......... .......... .......... .......... .......... 52%  179M 6s
134200K .......... .......... .......... .......... .......... 52%  954G 6s
134250K .......... .......... .......... .......... .......... 52%  142M 6s
134300K .......... .......... .......... .......... .......... 52%  101M 6s
134350K .......... .......... .......... .......... .......... 52%  234M 6s
134400K .......... .......... .......... .......... .......... 52%  234M 6s
134450K .......... .......... .......... .......... .......... 52%  954G 6s
134500K .......... .......... .......... .......... .......... 52%  239M 6s
134550K .......... .......... .......... .......... .......... 52% 92,8M 6s
134600K .......... .......... .......... .......... .......... 52% 78,2M 6s
134650K .......... .......... .......... .......... .......... 52%  954G 6s
134700K .......... .......... .......... .......... .......... 52% 74,6M 6s
134750K .......... .......... .......... .......... .......... 52% 80,8M 6s
134800K .......... .......... .......... .......... .......... 52% 59,2M 6s
134850K .......... .......... .......... .......... .......... 52% 93,9M 6s
134900K .......... .......... .......... .......... .......... 52%  954G 6s
134950K .......... .......... .......... .......... .......... 52%  269M 6s
135000K .......... .......... .......... .......... .......... 52%  194M 6s
135050K .......... .......... .......... .......... .......... 52%  311M 6s
135100K .......... .......... .......... .......... .......... 52%  362M 6s
135150K .......... .......... .......... .......... .......... 52% 48,3M 6s
135200K .......... .......... .......... .......... .......... 53% 10,4M 6s
135250K .......... .......... .......... .......... .......... 53% 28,4M 6s
135300K .......... .......... .......... .......... .......... 53% 29,1M 6s
135350K .......... .......... .......... .......... .......... 53% 47,7M 6s
135400K .......... .......... .......... .......... .......... 53% 18,5M 6s
135450K .......... .......... .......... .......... .......... 53% 24,3M 6s
135500K .......... .......... .......... .......... .......... 53% 35,6M 6s
135550K .......... .......... .......... .......... .......... 53% 30,4M 6s
135600K .......... .......... .......... .......... .......... 53% 27,8M 6s
135650K .......... .......... .......... .......... .......... 53% 34,7M 6s
135700K .......... .......... .......... .......... .......... 53% 53,8M 6s
135750K .......... .......... .......... .......... .......... 53% 26,0M 6s
135800K .......... .......... .......... .......... .......... 53% 17,5M 6s
135850K .......... .......... .......... .......... .......... 53% 21,6M 6s
135900K .......... .......... .......... .......... .......... 53% 34,2M 6s
135950K .......... .......... .......... .......... .......... 53% 32,9M 6s
136000K .......... .......... .......... .......... .......... 53% 37,5M 6s
136050K .......... .......... .......... .......... .......... 53% 32,5M 6s
136100K .......... .......... .......... .......... .......... 53% 27,3M 6s
136150K .......... .......... .......... .......... .......... 53% 38,5M 6s
136200K .......... .......... .......... .......... .......... 53% 35,8M 6s
136250K .......... .......... .......... .......... .......... 53% 13,9M 6s
136300K .......... .......... .......... .......... .......... 53% 19,1M 6s
136350K .......... .......... .......... .......... .......... 53% 31,5M 6s
136400K .......... .......... .......... .......... .......... 53% 35,7M 5s
136450K .......... .......... .......... .......... .......... 53% 34,8M 5s
136500K .......... .......... .......... .......... .......... 53% 30,8M 5s
136550K .......... .......... .......... .......... .......... 53% 22,8M 5s
136600K .......... .......... .......... .......... .......... 53% 59,2M 5s
136650K .......... .......... .......... .......... .......... 53% 16,0M 5s
136700K .......... .......... .......... .......... .......... 53% 33,0M 5s
136750K .......... .......... .......... .......... .......... 53% 33,6M 5s
136800K .......... .......... .......... .......... .......... 53% 28,7M 5s
136850K .......... .......... .......... .......... .......... 53% 29,0M 5s
136900K .......... .......... .......... .......... .......... 53% 40,3M 5s
136950K .......... .......... .......... .......... .......... 53% 28,9M 5s
137000K .......... .......... .......... .......... .......... 53% 24,5M 5s
137050K .......... .......... .......... .......... .......... 53% 20,6M 5s
137100K .......... .......... .......... .......... .......... 53% 34,5M 5s
137150K .......... .......... .......... .......... .......... 53% 38,0M 5s
137200K .......... .......... .......... .......... .......... 53% 37,6M 5s
137250K .......... .......... .......... .......... .......... 53% 25,7M 5s
137300K .......... .......... .......... .......... .......... 53% 18,2M 5s
137350K .......... .......... .......... .......... .......... 53% 32,5M 5s
137400K .......... .......... .......... .......... .......... 53% 33,7M 5s
137450K .......... .......... .......... .......... .......... 53% 9,20M 5s
137500K .......... .......... .......... .......... .......... 53% 38,6M 5s
137550K .......... .......... .......... .......... .......... 53% 16,4M 5s
137600K .......... .......... .......... .......... .......... 53% 43,9M 5s
137650K .......... .......... .......... .......... .......... 53% 4,31M 5s
137700K .......... .......... .......... .......... .......... 53%  219M 5s
137750K .......... .......... .......... .......... .......... 54%  216M 5s
137800K .......... .......... .......... .......... .......... 54% 1,28M 5s
137850K .......... .......... .......... .......... .......... 54%  195M 5s
137900K .......... .......... .......... .......... .......... 54% 54,7M 5s
137950K .......... .......... .......... .......... .......... 54%  351M 5s
138000K .......... .......... .......... .......... .......... 54% 17,8M 5s
138050K .......... .......... .......... .......... .......... 54%  342M 5s
138100K .......... .......... .......... .......... .......... 54%  166M 5s
138150K .......... .......... .......... .......... .......... 54% 23,3M 5s
138200K .......... .......... .......... .......... .......... 54% 32,9M 5s
138250K .......... .......... .......... .......... .......... 54% 27,2M 5s
138300K .......... .......... .......... .......... .......... 54% 47,3M 5s
138350K .......... .......... .......... .......... .......... 54% 64,0M 5s
138400K .......... .......... .......... .......... .......... 54%  954G 5s
138450K .......... .......... .......... .......... .......... 54% 10,4M 5s
138500K .......... .......... .......... .......... .......... 54%  954G 5s
138550K .......... .......... .......... .......... .......... 54% 57,1M 5s
138600K .......... .......... .......... .......... .......... 54%  954G 5s
138650K .......... .......... .......... .......... .......... 54% 7,69M 5s
138700K .......... .......... .......... .......... .......... 54% 69,0M 5s
138750K .......... .......... .......... .......... .......... 54% 9,97M 5s
138800K .......... .......... .......... .......... .......... 54% 56,7M 5s
138850K .......... .......... .......... .......... .......... 54% 42,5M 5s
138900K .......... .......... .......... .......... .......... 54% 25,1M 5s
138950K .......... .......... .......... .......... .......... 54% 63,9M 5s
139000K .......... .......... .......... .......... .......... 54% 22,8M 5s
139050K .......... .......... .......... .......... .......... 54% 79,0M 5s
139100K .......... .......... .......... .......... .......... 54%  250M 5s
139150K .......... .......... .......... .......... .......... 54% 76,0M 5s
139200K .......... .......... .......... .......... .......... 54%  289M 5s
139250K .......... .......... .......... .......... .......... 54%  159M 5s
139300K .......... .......... .......... .......... .......... 54% 85,8M 5s
139350K .......... .......... .......... .......... .......... 54%  954G 5s
139400K .......... .......... .......... .......... .......... 54%  282M 5s
139450K .......... .......... .......... .......... .......... 54%  368M 5s
139500K .......... .......... .......... .......... .......... 54%  384M 5s
139550K .......... .......... .......... .......... .......... 54%  954G 5s
139600K .......... .......... .......... .......... .......... 54%  216M 5s
139650K .......... .......... .......... .......... .......... 54%  387M 5s
139700K .......... .......... .......... .......... .......... 54%  192M 5s
139750K .......... .......... .......... .......... .......... 54%  341M 5s
139800K .......... .......... .......... .......... .......... 54%  954G 5s
139850K .......... .......... .......... .......... .......... 54%  376M 5s
139900K .......... .......... .......... .......... .......... 54%  201M 5s
139950K .......... .......... .......... .......... .......... 54% 18,1M 5s
140000K .......... .......... .......... .......... .......... 54% 18,2M 5s
140050K .......... .......... .......... .......... .......... 54% 38,6M 5s
140100K .......... .......... .......... .......... .......... 54% 35,5M 5s
140150K .......... .......... .......... .......... .......... 54% 38,7M 5s
140200K .......... .......... .......... .......... .......... 54% 37,2M 5s
140250K .......... .......... .......... .......... .......... 54% 35,4M 5s
140300K .......... .......... .......... .......... .......... 55% 42,7M 5s
140350K .......... .......... .......... .......... .......... 55% 10,9M 5s
140400K .......... .......... .......... .......... .......... 55% 60,5M 5s
140450K .......... .......... .......... .......... .......... 55% 12,0M 5s
140500K .......... .......... .......... .......... .......... 55% 40,6M 5s
140550K .......... .......... .......... .......... .......... 55% 37,8M 5s
140600K .......... .......... .......... .......... .......... 55% 35,8M 5s
140650K .......... .......... .......... .......... .......... 55% 37,5M 5s
140700K .......... .......... .......... .......... .......... 55% 35,2M 5s
140750K .......... .......... .......... .......... .......... 55% 12,4M 5s
140800K .......... .......... .......... .......... .......... 55% 36,6M 5s
140850K .......... .......... .......... .......... .......... 55% 1,72M 5s
140900K .......... .......... .......... .......... .......... 55%  137M 5s
140950K .......... .......... .......... .......... .......... 55% 74,8M 5s
141000K .......... .......... .......... .......... .......... 55% 25,4M 5s
141050K .......... .......... .......... .......... .......... 55% 11,1M 5s
141100K .......... .......... .......... .......... .......... 55% 78,0M 5s
141150K .......... .......... .......... .......... .......... 55%  196M 5s
141200K .......... .......... .......... .......... .......... 55% 22,1M 5s
141250K .......... .......... .......... .......... .......... 55% 12,4M 5s
141300K .......... .......... .......... .......... .......... 55%  954G 5s
141350K .......... .......... .......... .......... .......... 55%  207M 5s
141400K .......... .......... .......... .......... .......... 55%  390M 5s
141450K .......... .......... .......... .......... .......... 55%  406M 5s
141500K .......... .......... .......... .......... .......... 55%  410M 5s
141550K .......... .......... .......... .......... .......... 55%  954G 5s
141600K .......... .......... .......... .......... .......... 55%  335M 5s
141650K .......... .......... .......... .......... .......... 55%  195M 5s
141700K .......... .......... .......... .......... .......... 55%  372M 5s
141750K .......... .......... .......... .......... .......... 55%  358M 5s
141800K .......... .......... .......... .......... .......... 55%  954G 5s
141850K .......... .......... .......... .......... .......... 55%  219M 5s
141900K .......... .......... .......... .......... .......... 55%  350M 5s
141950K .......... .......... .......... .......... .......... 55%  335M 5s
142000K .......... .......... .......... .......... .......... 55% 45,1M 5s
142050K .......... .......... .......... .......... .......... 55% 18,0M 5s
142100K .......... .......... .......... .......... .......... 55%  112M 5s
142150K .......... .......... .......... .......... .......... 55% 12,4M 5s
142200K .......... .......... .......... .......... .......... 55% 35,1M 5s
142250K .......... .......... .......... .......... .......... 55% 39,8M 5s
142300K .......... .......... .......... .......... .......... 55% 30,8M 5s
142350K .......... .......... .......... .......... .......... 55% 34,9M 5s
142400K .......... .......... .......... .......... .......... 55% 19,5M 5s
142450K .......... .......... .......... .......... .......... 55% 18,1M 5s
142500K .......... .......... .......... .......... .......... 55% 37,1M 5s
142550K .......... .......... .......... .......... .......... 55% 96,9M 5s
142600K .......... .......... .......... .......... .......... 55% 18,8M 5s
142650K .......... .......... .......... .......... .......... 55% 39,0M 5s
142700K .......... .......... .......... .......... .......... 55% 35,7M 5s
142750K .......... .......... .......... .......... .......... 55% 42,4M 5s
142800K .......... .......... .......... .......... .......... 55% 22,0M 5s
142850K .......... .......... .......... .......... .......... 56% 20,1M 5s
142900K .......... .......... .......... .......... .......... 56% 34,6M 5s
142950K .......... .......... .......... .......... .......... 56% 25,6M 5s
143000K .......... .......... .......... .......... .......... 56% 33,9M 5s
143050K .......... .......... .......... .......... .......... 56% 36,5M 5s
143100K .......... .......... .......... .......... .......... 56% 14,0M 5s
143150K .......... .......... .......... .......... .......... 56% 45,5M 5s
143200K .......... .......... .......... .......... .......... 56% 24,4M 5s
143250K .......... .......... .......... .......... .......... 56% 11,0M 5s
143300K .......... .......... .......... .......... .......... 56% 36,7M 5s
143350K .......... .......... .......... .......... .......... 56% 31,1M 5s
143400K .......... .......... .......... .......... .......... 56% 38,6M 5s
143450K .......... .......... .......... .......... .......... 56% 44,9M 5s
143500K .......... .......... .......... .......... .......... 56% 17,9M 5s
143550K .......... .......... .......... .......... .......... 56% 30,0M 5s
143600K .......... .......... .......... .......... .......... 56% 13,6M 5s
143650K .......... .......... .......... .......... .......... 56% 25,4M 5s
143700K .......... .......... .......... .......... .......... 56% 28,7M 5s
143750K .......... .......... .......... .......... .......... 56% 37,3M 5s
143800K .......... .......... .......... .......... .......... 56% 28,3M 5s
143850K .......... .......... .......... .......... .......... 56% 32,9M 5s
143900K .......... .......... .......... .......... .......... 56% 44,7M 5s
143950K .......... .......... .......... .......... .......... 56% 23,9M 5s
144000K .......... .......... .......... .......... .......... 56% 29,9M 5s
144050K .......... .......... .......... .......... .......... 56% 15,7M 5s
144100K .......... .......... .......... .......... .......... 56% 18,8M 5s
144150K .......... .......... .......... .......... .......... 56% 26,8M 5s
144200K .......... .......... .......... .......... .......... 56% 41,1M 5s
144250K .......... .......... .......... .......... .......... 56% 37,7M 5s
144300K .......... .......... .......... .......... .......... 56% 30,8M 5s
144350K .......... .......... .......... .......... .......... 56% 48,3M 5s
144400K .......... .......... .......... .......... .......... 56% 1,33M 5s
144450K .......... .......... .......... .......... .......... 56%  214M 5s
144500K .......... .......... .......... .......... .......... 56% 17,9M 5s
144550K .......... .......... .......... .......... .......... 56% 16,3M 5s
144600K .......... .......... .......... .......... .......... 56%  285M 5s
144650K .......... .......... .......... .......... .......... 56% 20,7M 5s
144700K .......... .......... .......... .......... .......... 56%  954G 5s
144750K .......... .......... .......... .......... .......... 56%  278M 5s
144800K .......... .......... .......... .......... .......... 56%  378M 5s
144850K .......... .......... .......... .......... .......... 56% 5,84M 5s
144900K .......... .......... .......... .......... .......... 56% 27,0M 5s
144950K .......... .......... .......... .......... .......... 56% 64,8M 5s
145000K .......... .......... .......... .......... .......... 56%  224M 5s
145050K .......... .......... .......... .......... .......... 56% 38,4M 5s
145100K .......... .......... .......... .......... .......... 56% 38,4M 5s
145150K .......... .......... .......... .......... .......... 56%  287M 5s
145200K .......... .......... .......... .......... .......... 56% 7,67M 5s
145250K .......... .......... .......... .......... .......... 56%  283M 5s
145300K .......... .......... .......... .......... .......... 56% 18,0M 5s
145350K .......... .......... .......... .......... .......... 56%  222M 5s
145400K .......... .......... .......... .......... .......... 57%  173M 5s
145450K .......... .......... .......... .......... .......... 57%  954G 5s
145500K .......... .......... .......... .......... .......... 57%  115M 5s
145550K .......... .......... .......... .......... .......... 57%  202M 5s
145600K .......... .......... .......... .......... .......... 57%  105M 5s
145650K .......... .......... .......... .......... .......... 57%  187M 5s
145700K .......... .......... .......... .......... .......... 57%  954G 5s
145750K .......... .......... .......... .......... .......... 57%  131M 5s
145800K .......... .......... .......... .......... .......... 57%  342M 5s
145850K .......... .......... .......... .......... .......... 57%  308M 5s
145900K .......... .......... .......... .......... .......... 57%  954G 5s
145950K .......... .......... .......... .......... .......... 57%  358M 5s
146000K .......... .......... .......... .......... .......... 57%  397M 5s
146050K .......... .......... .......... .......... .......... 57%  246M 5s
146100K .......... .......... .......... .......... .......... 57%  285M 5s
146150K .......... .......... .......... .......... .......... 57%  954G 5s
146200K .......... .......... .......... .......... .......... 57%  349M 5s
146250K .......... .......... .......... .......... .......... 57% 29,9M 5s
146300K .......... .......... .......... .......... .......... 57% 16,4M 5s
146350K .......... .......... .......... .......... .......... 57% 36,4M 5s
146400K .......... .......... .......... .......... .......... 57% 37,5M 5s
146450K .......... .......... .......... .......... .......... 57% 20,8M 5s
146500K .......... .......... .......... .......... .......... 57% 39,3M 5s
146550K .......... .......... .......... .......... .......... 57% 25,0M 5s
146600K .......... .......... .......... .......... .......... 57% 13,7M 5s
146650K .......... .......... .......... .......... .......... 57%  127M 5s
146700K .......... .......... .......... .......... .......... 57% 28,6M 5s
146750K .......... .......... .......... .......... .......... 57% 24,0M 5s
146800K .......... .......... .......... .......... .......... 57% 36,1M 5s
146850K .......... .......... .......... .......... .......... 57% 28,2M 5s
146900K .......... .......... .......... .......... .......... 57% 37,5M 5s
146950K .......... .......... .......... .......... .......... 57% 29,4M 5s
147000K .......... .......... .......... .......... .......... 57% 39,7M 5s
147050K .......... .......... .......... .......... .......... 57% 11,5M 5s
147100K .......... .......... .......... .......... .......... 57% 23,0M 5s
147150K .......... .......... .......... .......... .......... 57% 34,4M 5s
147200K .......... .......... .......... .......... .......... 57% 42,2M 5s
147250K .......... .......... .......... .......... .......... 57% 35,4M 5s
147300K .......... .......... .......... .......... .......... 57% 33,1M 5s
147350K .......... .......... .......... .......... .......... 57% 40,7M 5s
147400K .......... .......... .......... .......... .......... 57% 29,8M 5s
147450K .......... .......... .......... .......... .......... 57% 19,9M 5s
147500K .......... .......... .......... .......... .......... 57% 30,4M 5s
147550K .......... .......... .......... .......... .......... 57% 39,0M 5s
147600K .......... .......... .......... .......... .......... 57% 36,4M 5s
147650K .......... .......... .......... .......... .......... 57% 32,8M 5s
147700K .......... .......... .......... .......... .......... 57% 39,1M 5s
147750K .......... .......... .......... .......... .......... 57% 35,6M 5s
147800K .......... .......... .......... .......... .......... 57% 35,8M 5s
147850K .......... .......... .......... .......... .......... 57% 37,9M 5s
147900K .......... .......... .......... .......... .......... 57% 17,6M 5s
147950K .......... .......... .......... .......... .......... 58% 33,8M 5s
148000K .......... .......... .......... .......... .......... 58% 41,8M 5s
148050K .......... .......... .......... .......... .......... 58% 32,5M 5s
148100K .......... .......... .......... .......... .......... 58% 44,3M 5s
148150K .......... .......... .......... .......... .......... 58% 36,5M 5s
148200K .......... .......... .......... .......... .......... 58% 21,2M 5s
148250K .......... .......... .......... .......... .......... 58% 40,5M 5s
148300K .......... .......... .......... .......... .......... 58% 22,3M 5s
148350K .......... .......... .......... .......... .......... 58% 18,8M 5s
148400K .......... .......... .......... .......... .......... 58% 33,5M 5s
148450K .......... .......... .......... .......... .......... 58% 25,2M 5s
148500K .......... .......... .......... .......... .......... 58% 27,7M 5s
148550K .......... .......... .......... .......... .......... 58% 39,7M 5s
148600K .......... .......... .......... .......... .......... 58% 16,5M 5s
148650K .......... .......... .......... .......... .......... 58% 23,2M 5s
148700K .......... .......... .......... .......... .......... 58% 26,7M 5s
148750K .......... .......... .......... .......... .......... 58% 9,37M 5s
148800K .......... .......... .......... .......... .......... 58% 38,6M 5s
148850K .......... .......... .......... .......... .......... 58% 27,8M 5s
148900K .......... .......... .......... .......... .......... 58% 34,3M 5s
148950K .......... .......... .......... .......... .......... 58% 32,0M 5s
149000K .......... .......... .......... .......... .......... 58% 18,6M 5s
149050K .......... .......... .......... .......... .......... 58% 37,1M 5s
149100K .......... .......... .......... .......... .......... 58% 1,24M 5s
149150K .......... .......... .......... .......... .......... 58%  355M 5s
149200K .......... .......... .......... .......... .......... 58%  954G 5s
149250K .......... .......... .......... .......... .......... 58%  337M 5s
149300K .......... .......... .......... .......... .......... 58% 8,92M 5s
149350K .......... .......... .......... .......... .......... 58%  168M 5s
149400K .......... .......... .......... .......... .......... 58% 20,2M 5s
149450K .......... .......... .......... .......... .......... 58%  954G 5s
149500K .......... .......... .......... .......... .......... 58% 1,05M 5s
149550K .......... .......... .......... .......... .......... 58%  954G 5s
149600K .......... .......... .......... .......... .......... 58%  170M 5s
149650K .......... .......... .......... .......... .......... 58%  383M 5s
149700K .......... .......... .......... .......... .......... 58%  120M 5s
149750K .......... .......... .......... .......... .......... 58% 74,7M 5s
149800K .......... .......... .......... .......... .......... 58%  954G 5s
149850K .......... .......... .......... .......... .......... 58%  194M 5s
149900K .......... .......... .......... .......... .......... 58%  271M 5s
149950K .......... .......... .......... .......... .......... 58% 67,7M 5s
150000K .......... .......... .......... .......... .......... 58%  954G 5s
150050K .......... .......... .......... .......... .......... 58%  110M 5s
150100K .......... .......... .......... .......... .......... 58%  167M 5s
150150K .......... .......... .......... .......... .......... 58%  171M 5s
150200K .......... .......... .......... .......... .......... 58%  138M 5s
150250K .......... .......... .......... .......... .......... 58%  954G 5s
150300K .......... .......... .......... .......... .......... 58%  126M 5s
150350K .......... .......... .......... .......... .......... 58% 78,3M 5s
150400K .......... .......... .......... .......... .......... 58%  104M 5s
150450K .......... .......... .......... .......... .......... 58% 70,3M 5s
150500K .......... .......... .......... .......... .......... 59%  954G 5s
150550K .......... .......... .......... .......... .......... 59% 48,6M 5s
150600K .......... .......... .......... .......... .......... 59% 97,3M 5s
150650K .......... .......... .......... .......... .......... 59%  283M 5s
150700K .......... .......... .......... .......... .......... 59%  954G 5s
150750K .......... .......... .......... .......... .......... 59%  191M 5s
150800K .......... .......... .......... .......... .......... 59%  359M 5s
150850K .......... .......... .......... .......... .......... 59%  390M 5s
150900K .......... .......... .......... .......... .......... 59%  384M 5s
150950K .......... .......... .......... .......... .......... 59%  954G 5s
151000K .......... .......... .......... .......... .......... 59%  373M 5s
151050K .......... .......... .......... .......... .......... 59%  365M 5s
151100K .......... .......... .......... .......... .......... 59%  384M 5s
151150K .......... .......... .......... .......... .......... 59%  954G 5s
151200K .......... .......... .......... .......... .......... 59%  372M 5s
151250K .......... .......... .......... .......... .......... 59%  289M 5s
151300K .......... .......... .......... .......... .......... 59%  191M 5s
151350K .......... .......... .......... .......... .......... 59%  364M 5s
151400K .......... .......... .......... .......... .......... 59%  954G 5s
151450K .......... .......... .......... .......... .......... 59%  124M 5s
151500K .......... .......... .......... .......... .......... 59% 33,1M 5s
151550K .......... .......... .......... .......... .......... 59% 66,3M 5s
151600K .......... .......... .......... .......... .......... 59%  954G 5s
151650K .......... .......... .......... .......... .......... 59%  199M 5s
151700K .......... .......... .......... .......... .......... 59% 73,7M 5s
151750K .......... .......... .......... .......... .......... 59% 67,7M 5s
151800K .......... .......... .......... .......... .......... 59%  134M 5s
151850K .......... .......... .......... .......... .......... 59%  223K 5s
151900K .......... .......... .......... .......... .......... 59% 54,7M 5s
151950K .......... .......... .......... .......... .......... 59%  100M 5s
152000K .......... .......... .......... .......... .......... 59%  954G 5s
152050K .......... .......... .......... .......... .......... 59% 94,0M 5s
152100K .......... .......... .......... .......... .......... 59%  186M 5s
152150K .......... .......... .......... .......... .......... 59%  324M 5s
152200K .......... .......... .......... .......... .......... 59%  954G 5s
152250K .......... .......... .......... .......... .......... 59%  103M 5s
152300K .......... .......... .......... .......... .......... 59%  284M 5s
152350K .......... .......... .......... .......... .......... 59% 85,6M 5s
152400K .......... .......... .......... .......... .......... 59% 70,1M 5s
152450K .......... .......... .......... .......... .......... 59% 46,4M 5s
152500K .......... .......... .......... .......... .......... 59% 26,1M 5s
152550K .......... .......... .......... .......... .......... 59% 17,8M 5s
152600K .......... .......... .......... .......... .......... 59% 9,68M 5s
152650K .......... .......... .......... .......... .......... 59% 31,2M 5s
152700K .......... .......... .......... .......... .......... 59% 47,0M 5s
152750K .......... .......... .......... .......... .......... 59% 20,8M 5s
152800K .......... .......... .......... .......... .......... 59% 64,1M 5s
152850K .......... .......... .......... .......... .......... 59% 51,0M 5s
152900K .......... .......... .......... .......... .......... 59% 31,3M 5s
152950K .......... .......... .......... .......... .......... 59% 66,3M 5s
153000K .......... .......... .......... .......... .......... 59% 32,0M 5s
153050K .......... .......... .......... .......... .......... 59% 49,5M 5s
153100K .......... .......... .......... .......... .......... 60% 38,2M 5s
153150K .......... .......... .......... .......... .......... 60% 33,6M 5s
153200K .......... .......... .......... .......... .......... 60% 30,1M 5s
153250K .......... .......... .......... .......... .......... 60% 33,4M 5s
153300K .......... .......... .......... .......... .......... 60% 23,0M 5s
153350K .......... .......... .......... .......... .......... 60% 23,2M 5s
153400K .......... .......... .......... .......... .......... 60% 30,3M 5s
153450K .......... .......... .......... .......... .......... 60% 41,7M 5s
153500K .......... .......... .......... .......... .......... 60% 27,9M 5s
153550K .......... .......... .......... .......... .......... 60% 42,8M 5s
153600K .......... .......... .......... .......... .......... 60%  200M 5s
153650K .......... .......... .......... .......... .......... 60%  954G 5s
153700K .......... .......... .......... .......... .......... 60%  349M 5s
153750K .......... .......... .......... .......... .......... 60%  406M 5s
153800K .......... .......... .......... .......... .......... 60%  211M 5s
153850K .......... .......... .......... .......... .......... 60%  229M 5s
153900K .......... .......... .......... .......... .......... 60%  954G 5s
153950K .......... .......... .......... .......... .......... 60%  342M 5s
154000K .......... .......... .......... .......... .......... 60%  410M 5s
154050K .......... .......... .......... .......... .......... 60%  164M 5s
154100K .......... .......... .......... .......... .......... 60% 31,4M 5s
154150K .......... .......... .......... .......... .......... 60% 23,3M 5s
154200K .......... .......... .......... .......... .......... 60% 20,2M 5s
154250K .......... .......... .......... .......... .......... 60% 41,0M 5s
154300K .......... .......... .......... .......... .......... 60% 34,1M 5s
154350K .......... .......... .......... .......... .......... 60% 28,8M 5s
154400K .......... .......... .......... .......... .......... 60% 34,6M 5s
154450K .......... .......... .......... .......... .......... 60% 19,8M 5s
154500K .......... .......... .......... .......... .......... 60% 22,4M 5s
154550K .......... .......... .......... .......... .......... 60% 31,0M 5s
154600K .......... .......... .......... .......... .......... 60% 17,1M 5s
154650K .......... .......... .......... .......... .......... 60% 40,7M 5s
154700K .......... .......... .......... .......... .......... 60% 26,3M 5s
154750K .......... .......... .......... .......... .......... 60% 19,1M 5s
154800K .......... .......... .......... .......... .......... 60% 30,9M 5s
154850K .......... .......... .......... .......... .......... 60% 27,8M 5s
154900K .......... .......... .......... .......... .......... 60% 9,19M 5s
154950K .......... .......... .......... .......... .......... 60% 39,7M 5s
155000K .......... .......... .......... .......... .......... 60% 18,7M 5s
155050K .......... .......... .......... .......... .......... 60% 29,4M 5s
155100K .......... .......... .......... .......... .......... 60% 16,8M 5s
155150K .......... .......... .......... .......... .......... 60% 27,5M 5s
155200K .......... .......... .......... .......... .......... 60% 37,3M 5s
155250K .......... .......... .......... .......... .......... 60% 30,1M 5s
155300K .......... .......... .......... .......... .......... 60% 17,6M 5s
155350K .......... .......... .......... .......... .......... 60% 5,81M 5s
155400K .......... .......... .......... .......... .......... 60% 13,6M 5s
155450K .......... .......... .......... .......... .......... 60% 65,7M 5s
155500K .......... .......... .......... .......... .......... 60% 26,3M 5s
155550K .......... .......... .......... .......... .......... 60% 23,2M 5s
155600K .......... .......... .......... .......... .......... 60% 17,3M 5s
155650K .......... .......... .......... .......... .......... 61% 40,3M 5s
155700K .......... .......... .......... .......... .......... 61% 30,9M 5s
155750K .......... .......... .......... .......... .......... 61% 38,9M 5s
155800K .......... .......... .......... .......... .......... 61% 32,8M 5s
155850K .......... .......... .......... .......... .......... 61% 12,7M 5s
155900K .......... .......... .......... .......... .......... 61% 28,9M 5s
155950K .......... .......... .......... .......... .......... 61% 36,7M 5s
156000K .......... .......... .......... .......... .......... 61% 21,5M 5s
156050K .......... .......... .......... .......... .......... 61% 38,3M 5s
156100K .......... .......... .......... .......... .......... 61% 28,3M 5s
156150K .......... .......... .......... .......... .......... 61% 16,7M 5s
156200K .......... .......... .......... .......... .......... 61% 47,2M 5s
156250K .......... .......... .......... .......... .......... 61% 31,7M 5s
156300K .......... .......... .......... .......... .......... 61% 37,2M 5s
156350K .......... .......... .......... .......... .......... 61% 34,1M 5s
156400K .......... .......... .......... .......... .......... 61% 29,1M 5s
156450K .......... .......... .......... .......... .......... 61% 30,5M 5s
156500K .......... .......... .......... .......... .......... 61% 28,7M 5s
156550K .......... .......... .......... .......... .......... 61% 16,5M 5s
156600K .......... .......... .......... .......... .......... 61% 48,6M 5s
156650K .......... .......... .......... .......... .......... 61% 34,9M 5s
156700K .......... .......... .......... .......... .......... 61% 24,6M 5s
156750K .......... .......... .......... .......... .......... 61% 37,8M 5s
156800K .......... .......... .......... .......... .......... 61% 35,3M 5s
156850K .......... .......... .......... .......... .......... 61% 35,4M 5s
156900K .......... .......... .......... .......... .......... 61% 32,4M 5s
156950K .......... .......... .......... .......... .......... 61% 29,6M 5s
157000K .......... .......... .......... .......... .......... 61% 9,65M 5s
157050K .......... .......... .......... .......... .......... 61%  102M 5s
157100K .......... .......... .......... .......... .......... 61% 25,3M 5s
157150K .......... .......... .......... .......... .......... 61% 17,6M 5s
157200K .......... .......... .......... .......... .......... 61% 36,3M 5s
157250K .......... .......... .......... .......... .......... 61% 38,0M 5s
157300K .......... .......... .......... .......... .......... 61% 30,7M 5s
157350K .......... .......... .......... .......... .......... 61% 32,3M 5s
157400K .......... .......... .......... .......... .......... 61% 43,3M 5s
157450K .......... .......... .......... .......... .......... 61% 18,5M 5s
157500K .......... .......... .......... .......... .......... 61% 25,4M 5s
157550K .......... .......... .......... .......... .......... 61% 28,0M 5s
157600K .......... .......... .......... .......... .......... 61% 20,1M 5s
157650K .......... .......... .......... .......... .......... 61% 31,7M 5s
157700K .......... .......... .......... .......... .......... 61% 36,5M 5s
157750K .......... .......... .......... .......... .......... 61% 34,2M 5s
157800K .......... .......... .......... .......... .......... 61% 36,6M 5s
157850K .......... .......... .......... .......... .......... 61% 38,0M 5s
157900K .......... .......... .......... .......... .......... 61% 20,4M 5s
157950K .......... .......... .......... .......... .......... 61% 40,8M 5s
158000K .......... .......... .......... .......... .......... 61% 16,5M 5s
158050K .......... .......... .......... .......... .......... 61% 36,9M 4s
158100K .......... .......... .......... .......... .......... 61% 29,6M 4s
158150K .......... .......... .......... .......... .......... 61% 27,6M 4s
158200K .......... .......... .......... .......... .......... 62% 30,4M 4s
158250K .......... .......... .......... .......... .......... 62% 14,5M 4s
158300K .......... .......... .......... .......... .......... 62% 35,3M 4s
158350K .......... .......... .......... .......... .......... 62% 24,9M 4s
158400K .......... .......... .......... .......... .......... 62% 13,6M 4s
158450K .......... .......... .......... .......... .......... 62% 30,0M 4s
158500K .......... .......... .......... .......... .......... 62% 31,2M 4s
158550K .......... .......... .......... .......... .......... 62% 33,7M 4s
158600K .......... .......... .......... .......... .......... 62% 28,5M 4s
158650K .......... .......... .......... .......... .......... 62% 34,6M 4s
158700K .......... .......... .......... .......... .......... 62% 36,8M 4s
158750K .......... .......... .......... .......... .......... 62% 29,6M 4s
158800K .......... .......... .......... .......... .......... 62% 10,7M 4s
158850K .......... .......... .......... .......... .......... 62% 38,9M 4s
158900K .......... .......... .......... .......... .......... 62% 34,7M 4s
158950K .......... .......... .......... .......... .......... 62% 35,3M 4s
159000K .......... .......... .......... .......... .......... 62% 15,9M 4s
159050K .......... .......... .......... .......... .......... 62% 34,8M 4s
159100K .......... .......... .......... .......... .......... 62% 30,5M 4s
159150K .......... .......... .......... .......... .......... 62% 27,7M 4s
159200K .......... .......... .......... .......... .......... 62% 38,2M 4s
159250K .......... .......... .......... .......... .......... 62% 19,0M 4s
159300K .......... .......... .......... .......... .......... 62% 29,2M 4s
159350K .......... .......... .......... .......... .......... 62% 30,5M 4s
159400K .......... .......... .......... .......... .......... 62% 1,01M 4s
159450K .......... .......... .......... .......... .......... 62%  300M 4s
159500K .......... .......... .......... .......... .......... 62%  306M 4s
159550K .......... .......... .......... .......... .......... 62%  403M 4s
159600K .......... .......... .......... .......... .......... 62%  954G 4s
159650K .......... .......... .......... .......... .......... 62%  395M 4s
159700K .......... .......... .......... .......... .......... 62%  420M 4s
159750K .......... .......... .......... .......... .......... 62%  314M 4s
159800K .......... .......... .......... .......... .......... 62%  202M 4s
159850K .......... .......... .......... .......... .......... 62%  954G 4s
159900K .......... .......... .......... .......... .......... 62%  339M 4s
159950K .......... .......... .......... .......... .......... 62%  226M 4s
160000K .......... .......... .......... .......... .......... 62%  318M 4s
160050K .......... .......... .......... .......... .......... 62%  954G 4s
160100K .......... .......... .......... .......... .......... 62% 1,72M 4s
160150K .......... .......... .......... .......... .......... 62%  336M 4s
160200K .......... .......... .......... .......... .......... 62%  954G 4s
160250K .......... .......... .......... .......... .......... 62%  179M 4s
160300K .......... .......... .......... .......... .......... 62% 7,65M 4s
160350K .......... .......... .......... .......... .......... 62% 13,4M 4s
160400K .......... .......... .......... .......... .......... 62%  954G 4s
160450K .......... .......... .......... .......... .......... 62%  350M 4s
160500K .......... .......... .......... .......... .......... 62%  152M 4s
160550K .......... .......... .......... .......... .......... 62%  197M 4s
160600K .......... .......... .......... .......... .......... 62% 5,38M 4s
160650K .......... .......... .......... .......... .......... 62% 28,7M 4s
160700K .......... .......... .......... .......... .......... 62%  173M 4s
160750K .......... .......... .......... .......... .......... 63%  954G 4s
160800K .......... .......... .......... .......... .......... 63%  109M 4s
160850K .......... .......... .......... .......... .......... 63%  310M 4s
160900K .......... .......... .......... .......... .......... 63%  366M 4s
160950K .......... .......... .......... .......... .......... 63%  954G 4s
161000K .......... .......... .......... .......... .......... 63%  369M 4s
161050K .......... .......... .......... .......... .......... 63%  386M 4s
161100K .......... .......... .......... .......... .......... 63%  390M 4s
161150K .......... .......... .......... .......... .......... 63%  390M 4s
161200K .......... .......... .......... .......... .......... 63%  954G 4s
161250K .......... .......... .......... .......... .......... 63%  396M 4s
161300K .......... .......... .......... .......... .......... 63%  395M 4s
161350K .......... .......... .......... .......... .......... 63%  393M 4s
161400K .......... .......... .......... .......... .......... 63%  197M 4s
161450K .......... .......... .......... .......... .......... 63%  954G 4s
161500K .......... .......... .......... .......... .......... 63%  354M 4s
161550K .......... .......... .......... .......... .......... 63%  372M 4s
161600K .......... .......... .......... .......... .......... 63%  390M 4s
161650K .......... .......... .......... .......... .......... 63%  954G 4s
161700K .......... .......... .......... .......... .......... 63%  402M 4s
161750K .......... .......... .......... .......... .......... 63%  252M 4s
161800K .......... .......... .......... .......... .......... 63%  280M 4s
161850K .......... .......... .......... .......... .......... 63%  403M 4s
161900K .......... .......... .......... .......... .......... 63%  954G 4s
161950K .......... .......... .......... .......... .......... 63%  388M 4s
162000K .......... .......... .......... .......... .......... 63% 49,5M 4s
162050K .......... .......... .......... .......... .......... 63% 32,6M 4s
162100K .......... .......... .......... .......... .......... 63% 15,0M 4s
162150K .......... .......... .......... .......... .......... 63% 25,1M 4s
162200K .......... .......... .......... .......... .......... 63% 42,1M 4s
162250K .......... .......... .......... .......... .......... 63% 19,6M 4s
162300K .......... .......... .......... .......... .......... 63% 20,7M 4s
162350K .......... .......... .......... .......... .......... 63% 18,5M 4s
162400K .......... .......... .......... .......... .......... 63% 25,4M 4s
162450K .......... .......... .......... .......... .......... 63% 41,6M 4s
162500K .......... .......... .......... .......... .......... 63% 10,4M 4s
162550K .......... .......... .......... .......... .......... 63% 51,7M 4s
162600K .......... .......... .......... .......... .......... 63% 26,9M 4s
162650K .......... .......... .......... .......... .......... 63% 11,4M 4s
162700K .......... .......... .......... .......... .......... 63% 37,0M 4s
162750K .......... .......... .......... .......... .......... 63% 23,9M 4s
162800K .......... .......... .......... .......... .......... 63% 36,5M 4s
162850K .......... .......... .......... .......... .......... 63% 27,4M 4s
162900K .......... .......... .......... .......... .......... 63% 40,9M 4s
162950K .......... .......... .......... .......... .......... 63% 15,7M 4s
163000K .......... .......... .......... .......... .......... 63% 32,0M 4s
163050K .......... .......... .......... .......... .......... 63% 15,0M 4s
163100K .......... .......... .......... .......... .......... 63% 34,2M 4s
163150K .......... .......... .......... .......... .......... 63% 36,8M 4s
163200K .......... .......... .......... .......... .......... 63% 42,5M 4s
163250K .......... .......... .......... .......... .......... 63% 25,6M 4s
163300K .......... .......... .......... .......... .......... 64% 36,5M 4s
163350K .......... .......... .......... .......... .......... 64% 40,9M 4s
163400K .......... .......... .......... .......... .......... 64% 30,0M 4s
163450K .......... .......... .......... .......... .......... 64% 17,3M 4s
163500K .......... .......... .......... .......... .......... 64% 36,4M 4s
163550K .......... .......... .......... .......... .......... 64% 30,8M 4s
163600K .......... .......... .......... .......... .......... 64% 12,2M 4s
163650K .......... .......... .......... .......... .......... 64% 1,32M 4s
163700K .......... .......... .......... .......... .......... 64% 49,5M 4s
163750K .......... .......... .......... .......... .......... 64% 20,8M 4s
163800K .......... .......... .......... .......... .......... 64% 61,7M 4s
163850K .......... .......... .......... .......... .......... 64%  238M 4s
163900K .......... .......... .......... .......... .......... 64% 26,7M 4s
163950K .......... .......... .......... .......... .......... 64% 48,0M 4s
164000K .......... .......... .......... .......... .......... 64%  282M 4s
164050K .......... .......... .......... .......... .......... 64% 23,5M 4s
164100K .......... .......... .......... .......... .......... 64%  289M 4s
164150K .......... .......... .......... .......... .......... 64%  954G 4s
164200K .......... .......... .......... .......... .......... 64%  361M 4s
164250K .......... .......... .......... .......... .......... 64%  360M 4s
164300K .......... .......... .......... .......... .......... 64% 4,26M 4s
164350K .......... .......... .......... .......... .......... 64% 31,7M 4s
164400K .......... .......... .......... .......... .......... 64% 25,1M 4s
164450K .......... .......... .......... .......... .......... 64% 24,2M 4s
164500K .......... .......... .......... .......... .......... 64%  954G 4s
164550K .......... .......... .......... .......... .......... 64%  268M 4s
164600K .......... .......... .......... .......... .......... 64%  334M 4s
164650K .......... .......... .......... .......... .......... 64%  192M 4s
164700K .......... .......... .......... .......... .......... 64%  954G 4s
164750K .......... .......... .......... .......... .......... 64%  366M 4s
164800K .......... .......... .......... .......... .......... 64%  310M 4s
164850K .......... .......... .......... .......... .......... 64%  252M 4s
164900K .......... .......... .......... .......... .......... 64%  382M 4s
164950K .......... .......... .......... .......... .......... 64%  954G 4s
165000K .......... .......... .......... .......... .......... 64%  215M 4s
165050K .......... .......... .......... .......... .......... 64%  416M 4s
165100K .......... .......... .......... .......... .......... 64%  243M 4s
165150K .......... .......... .......... .......... .......... 64%  954G 4s
165200K .......... .......... .......... .......... .......... 64%  321M 4s
165250K .......... .......... .......... .......... .......... 64%  218M 4s
165300K .......... .......... .......... .......... .......... 64% 36,3M 4s
165350K .......... .......... .......... .......... .......... 64% 4,48M 4s
165400K .......... .......... .......... .......... .......... 64% 35,2M 4s
165450K .......... .......... .......... .......... .......... 64% 40,8M 4s
165500K .......... .......... .......... .......... .......... 64% 26,4M 4s
165550K .......... .......... .......... .......... .......... 64% 33,5M 4s
165600K .......... .......... .......... .......... .......... 64% 34,8M 4s
165650K .......... .......... .......... .......... .......... 64% 29,8M 4s
165700K .......... .......... .......... .......... .......... 64% 35,9M 4s
165750K .......... .......... .......... .......... .......... 64% 15,9M 4s
165800K .......... .......... .......... .......... .......... 64% 30,6M 4s
165850K .......... .......... .......... .......... .......... 65% 34,5M 4s
165900K .......... .......... .......... .......... .......... 65% 36,4M 4s
165950K .......... .......... .......... .......... .......... 65% 29,7M 4s
166000K .......... .......... .......... .......... .......... 65% 48,6M 4s
166050K .......... .......... .......... .......... .......... 65% 32,1M 4s
166100K .......... .......... .......... .......... .......... 65% 16,8M 4s
166150K .......... .......... .......... .......... .......... 65% 35,5M 4s
166200K .......... .......... .......... .......... .......... 65% 14,7M 4s
166250K .......... .......... .......... .......... .......... 65% 33,2M 4s
166300K .......... .......... .......... .......... .......... 65% 26,0M 4s
166350K .......... .......... .......... .......... .......... 65% 51,6M 4s
166400K .......... .......... .......... .......... .......... 65% 36,4M 4s
166450K .......... .......... .......... .......... .......... 65% 31,2M 4s
166500K .......... .......... .......... .......... .......... 65% 42,6M 4s
166550K .......... .......... .......... .......... .......... 65% 33,5M 4s
166600K .......... .......... .......... .......... .......... 65% 39,3M 4s
166650K .......... .......... .......... .......... .......... 65% 17,7M 4s
166700K .......... .......... .......... .......... .......... 65% 32,0M 4s
166750K .......... .......... .......... .......... .......... 65% 28,1M 4s
166800K .......... .......... .......... .......... .......... 65% 29,3M 4s
166850K .......... .......... .......... .......... .......... 65% 22,1M 4s
166900K .......... .......... .......... .......... .......... 65% 68,5M 4s
166950K .......... .......... .......... .......... .......... 65% 31,4M 4s
167000K .......... .......... .......... .......... .......... 65% 44,8M 4s
167050K .......... .......... .......... .......... .......... 65% 14,8M 4s
167100K .......... .......... .......... .......... .......... 65% 36,1M 4s
167150K .......... .......... .......... .......... .......... 65% 29,6M 4s
167200K .......... .......... .......... .......... .......... 65% 21,2M 4s
167250K .......... .......... .......... .......... .......... 65% 27,6M 4s
167300K .......... .......... .......... .......... .......... 65% 12,9M 4s
167350K .......... .......... .......... .......... .......... 65% 3,23M 4s
167400K .......... .......... .......... .......... .......... 65%  232M 4s
167450K .......... .......... .......... .......... .......... 65%  134M 4s
167500K .......... .......... .......... .......... .......... 65% 81,7M 4s
167550K .......... .......... .......... .......... .......... 65%  100M 4s
167600K .......... .......... .......... .......... .......... 65%  156M 4s
167650K .......... .......... .......... .......... .......... 65%  149M 4s
167700K .......... .......... .......... .......... .......... 65%  131M 4s
167750K .......... .......... .......... .......... .......... 65%  123M 4s
167800K .......... .......... .......... .......... .......... 65% 81,6M 4s
167850K .......... .......... .......... .......... .......... 65%  146M 4s
167900K .......... .......... .......... .......... .......... 65%  155M 4s
167950K .......... .......... .......... .......... .......... 65% 93,4M 4s
168000K .......... .......... .......... .......... .......... 65% 17,4M 4s
168050K .......... .......... .......... .......... .......... 65% 8,73M 4s
168100K .......... .......... .......... .......... .......... 65% 32,0M 4s
168150K .......... .......... .......... .......... .......... 65% 23,9M 4s
168200K .......... .......... .......... .......... .......... 65% 58,6M 4s
168250K .......... .......... .......... .......... .......... 65% 33,8M 4s
168300K .......... .......... .......... .......... .......... 65% 29,6M 4s
168350K .......... .......... .......... .......... .......... 65% 40,7M 4s
168400K .......... .......... .......... .......... .......... 66% 28,8M 4s
168450K .......... .......... .......... .......... .......... 66% 17,1M 4s
168500K .......... .......... .......... .......... .......... 66% 24,0M 4s
168550K .......... .......... .......... .......... .......... 66% 48,7M 4s
168600K .......... .......... .......... .......... .......... 66% 1,11M 4s
168650K .......... .......... .......... .......... .......... 66% 29,4M 4s
168700K .......... .......... .......... .......... .......... 66%  157M 4s
168750K .......... .......... .......... .......... .......... 66%  198M 4s
168800K .......... .......... .......... .......... .......... 66% 20,2M 4s
168850K .......... .......... .......... .......... .......... 66% 32,7M 4s
168900K .......... .......... .......... .......... .......... 66% 30,2M 4s
168950K .......... .......... .......... .......... .......... 66% 20,8M 4s
169000K .......... .......... .......... .......... .......... 66%  954G 4s
169050K .......... .......... .......... .......... .......... 66%  361M 4s
169100K .......... .......... .......... .......... .......... 66% 7,95M 4s
169150K .......... .......... .......... .......... .......... 66%  954G 4s
169200K .......... .......... .......... .......... .......... 66%  156M 4s
169250K .......... .......... .......... .......... .......... 66%  337M 4s
169300K .......... .......... .......... .......... .......... 66%  413M 4s
169350K .......... .......... .......... .......... .......... 66%  954G 4s
169400K .......... .......... .......... .......... .......... 66%  404M 4s
169450K .......... .......... .......... .......... .......... 66%  398M 4s
169500K .......... .......... .......... .......... .......... 66%  406M 4s
169550K .......... .......... .......... .......... .......... 66%  419M 4s
169600K .......... .......... .......... .......... .......... 66%  954G 4s
169650K .......... .......... .......... .......... .......... 66%  413M 4s
169700K .......... .......... .......... .......... .......... 66%  201M 4s
169750K .......... .......... .......... .......... .......... 66%  192M 4s
169800K .......... .......... .......... .......... .......... 66%  954G 4s
169850K .......... .......... .......... .......... .......... 66%  401M 4s
169900K .......... .......... .......... .......... .......... 66%  394M 4s
169950K .......... .......... .......... .......... .......... 66%  370M 4s
170000K .......... .......... .......... .......... .......... 66%  311M 4s
170050K .......... .......... .......... .......... .......... 66%  954G 4s
170100K .......... .......... .......... .......... .......... 66%  243M 4s
170150K .......... .......... .......... .......... .......... 66%  354M 4s
170200K .......... .......... .......... .......... .......... 66%  384M 4s
170250K .......... .......... .......... .......... .......... 66% 13,0M 4s
170300K .......... .......... .......... .......... .......... 66% 29,9M 4s
170350K .......... .......... .......... .......... .......... 66% 27,9M 4s
170400K .......... .......... .......... .......... .......... 66% 54,9M 4s
170450K .......... .......... .......... .......... .......... 66% 17,3M 4s
170500K .......... .......... .......... .......... .......... 66% 36,0M 4s
170550K .......... .......... .......... .......... .......... 66% 6,70M 4s
170600K .......... .......... .......... .......... .......... 66% 32,0M 4s
170650K .......... .......... .......... .......... .......... 66% 30,0M 4s
170700K .......... .......... .......... .......... .......... 66% 10,9M 4s
170750K .......... .......... .......... .......... .......... 66% 15,1M 4s
170800K .......... .......... .......... .......... .......... 66% 21,7M 4s
170850K .......... .......... .......... .......... .......... 66% 27,0M 4s
170900K .......... .......... .......... .......... .......... 66% 23,4M 4s
170950K .......... .......... .......... .......... .......... 67% 61,5M 4s
171000K .......... .......... .......... .......... .......... 67% 30,1M 4s
171050K .......... .......... .......... .......... .......... 67% 28,8M 4s
171100K .......... .......... .......... .......... .......... 67% 28,6M 4s
171150K .......... .......... .......... .......... .......... 67% 15,2M 4s
171200K .......... .......... .......... .......... .......... 67% 38,2M 4s
171250K .......... .......... .......... .......... .......... 67% 36,8M 4s
171300K .......... .......... .......... .......... .......... 67% 30,2M 4s
171350K .......... .......... .......... .......... .......... 67% 38,4M 4s
171400K .......... .......... .......... .......... .......... 67% 15,4M 4s
171450K .......... .......... .......... .......... .......... 67% 46,4M 4s
171500K .......... .......... .......... .......... .......... 67% 25,4M 4s
171550K .......... .......... .......... .......... .......... 67% 18,6M 4s
171600K .......... .......... .......... .......... .......... 67% 35,7M 4s
171650K .......... .......... .......... .......... .......... 67% 23,2M 4s
171700K .......... .......... .......... .......... .......... 67% 25,2M 4s
171750K .......... .......... .......... .......... .......... 67% 47,2M 4s
171800K .......... .......... .......... .......... .......... 67% 34,1M 4s
171850K .......... .......... .......... .......... .......... 67% 30,4M 4s
171900K .......... .......... .......... .......... .......... 67% 39,4M 4s
171950K .......... .......... .......... .......... .......... 67% 21,2M 4s
172000K .......... .......... .......... .......... .......... 67% 23,0M 4s
172050K .......... .......... .......... .......... .......... 67% 28,2M 4s
172100K .......... .......... .......... .......... .......... 67% 41,7M 4s
172150K .......... .......... .......... .......... .......... 67% 33,8M 4s
172200K .......... .......... .......... .......... .......... 67% 13,4M 4s
172250K .......... .......... .......... .......... .......... 67% 30,0M 4s
172300K .......... .......... .......... .......... .......... 67% 36,0M 4s
172350K .......... .......... .......... .......... .......... 67% 27,0M 4s
172400K .......... .......... .......... .......... .......... 67% 11,0M 4s
172450K .......... .......... .......... .......... .......... 67% 28,0M 4s
172500K .......... .......... .......... .......... .......... 67% 33,2M 4s
172550K .......... .......... .......... .......... .......... 67% 42,6M 4s
172600K .......... .......... .......... .......... .......... 67% 29,7M 4s
172650K .......... .......... .......... .......... .......... 67% 30,4M 4s
172700K .......... .......... .......... .......... .......... 67% 8,87M 4s
172750K .......... .......... .......... .......... .......... 67% 70,9M 4s
172800K .......... .......... .......... .......... .......... 67% 46,3M 4s
172850K .......... .......... .......... .......... .......... 67% 35,3M 4s
172900K .......... .......... .......... .......... .......... 67% 36,1M 4s
172950K .......... .......... .......... .......... .......... 67% 35,3M 4s
173000K .......... .......... .......... .......... .......... 67% 29,0M 4s
173050K .......... .......... .......... .......... .......... 67% 17,0M 4s
173100K .......... .......... .......... .......... .......... 67% 32,7M 4s
173150K .......... .......... .......... .......... .......... 67% 39,5M 4s
173200K .......... .......... .......... .......... .......... 67% 17,5M 4s
173250K .......... .......... .......... .......... .......... 67% 29,2M 4s
173300K .......... .......... .......... .......... .......... 67% 35,7M 4s
173350K .......... .......... .......... .......... .......... 67% 30,7M 4s
173400K .......... .......... .......... .......... .......... 67% 41,5M 4s
173450K .......... .......... .......... .......... .......... 67% 16,3M 4s
173500K .......... .......... .......... .......... .......... 68% 16,9M 4s
173550K .......... .......... .......... .......... .......... 68% 24,7M 4s
173600K .......... .......... .......... .......... .......... 68% 32,4M 4s
173650K .......... .......... .......... .......... .......... 68% 18,5M 4s
173700K .......... .......... .......... .......... .......... 68% 40,0M 4s
173750K .......... .......... .......... .......... .......... 68% 16,2M 4s
173800K .......... .......... .......... .......... .......... 68% 33,2M 4s
173850K .......... .......... .......... .......... .......... 68% 35,2M 4s
173900K .......... .......... .......... .......... .......... 68% 19,9M 4s
173950K .......... .......... .......... .......... .......... 68% 38,6M 4s
174000K .......... .......... .......... .......... .......... 68% 1,17M 4s
174050K .......... .......... .......... .......... .......... 68% 30,6M 4s
174100K .......... .......... .......... .......... .......... 68% 70,9M 4s
174150K .......... .......... .......... .......... .......... 68%  374M 4s
174200K .......... .......... .......... .......... .......... 68% 33,1M 4s
174250K .......... .......... .......... .......... .......... 68%  297M 4s
174300K .......... .......... .......... .......... .......... 68%  245M 4s
174350K .......... .......... .......... .......... .......... 68%  954G 4s
174400K .......... .......... .......... .......... .......... 68%  357M 4s
174450K .......... .......... .......... .......... .......... 68%  378M 4s
174500K .......... .......... .......... .......... .......... 68%  415M 4s
174550K .......... .......... .......... .......... .......... 68%  119M 4s
174600K .......... .......... .......... .......... .......... 68%  954G 4s
174650K .......... .......... .......... .......... .......... 68%  188M 4s
174700K .......... .......... .......... .......... .......... 68%  229M 4s
174750K .......... .......... .......... .......... .......... 68%  218M 4s
174800K .......... .......... .......... .......... .......... 68%  954G 4s
174850K .......... .......... .......... .......... .......... 68%  169M 4s
174900K .......... .......... .......... .......... .......... 68%  233M 4s
174950K .......... .......... .......... .......... .......... 68%  238M 4s
175000K .......... .......... .......... .......... .......... 68%  239M 4s
175050K .......... .......... .......... .......... .......... 68%  954G 4s
175100K .......... .......... .......... .......... .......... 68%  117M 4s
175150K .......... .......... .......... .......... .......... 68%  156M 4s
175200K .......... .......... .......... .......... .......... 68% 52,7M 4s
175250K .......... .......... .......... .......... .......... 68% 31,2M 4s
175300K .......... .......... .......... .......... .......... 68%  954G 4s
175350K .......... .......... .......... .......... .......... 68% 43,5M 4s
175400K .......... .......... .......... .......... .......... 68% 24,7M 4s
175450K .......... .......... .......... .......... .......... 68% 40,6M 4s
175500K .......... .......... .......... .......... .......... 68% 7,93M 4s
175550K .......... .......... .......... .......... .......... 68% 17,1M 4s
175600K .......... .......... .......... .......... .......... 68% 11,6M 4s
175650K .......... .......... .......... .......... .......... 68% 10,9M 4s
175700K .......... .......... .......... .......... .......... 68% 31,3M 4s
175750K .......... .......... .......... .......... .......... 68% 37,5M 4s
175800K .......... .......... .......... .......... .......... 68% 27,2M 4s
175850K .......... .......... .......... .......... .......... 68% 18,2M 4s
175900K .......... .......... .......... .......... .......... 68% 2,78M 4s
175950K .......... .......... .......... .......... .......... 68% 25,7M 4s
176000K .......... .......... .......... .......... .......... 68% 31,8M 4s
176050K .......... .......... .......... .......... .......... 69%  954G 4s
176100K .......... .......... .......... .......... .......... 69% 39,5M 4s
176150K .......... .......... .......... .......... .......... 69% 71,3M 4s
176200K .......... .......... .......... .......... .......... 69% 64,6M 4s
176250K .......... .......... .......... .......... .......... 69%  954G 4s
176300K .......... .......... .......... .......... .......... 69%  207M 4s
176350K .......... .......... .......... .......... .......... 69% 82,6M 4s
176400K .......... .......... .......... .......... .......... 69% 51,0M 4s
176450K .......... .......... .......... .......... .......... 69% 40,3M 4s
176500K .......... .......... .......... .......... .......... 69%  954G 4s
176550K .......... .......... .......... .......... .......... 69% 43,5M 4s
176600K .......... .......... .......... .......... .......... 69% 40,4M 4s
176650K .......... .......... .......... .......... .......... 69% 42,3M 4s
176700K .......... .......... .......... .......... .......... 69% 30,4M 4s
176750K .......... .......... .......... .......... .......... 69% 28,4M 4s
176800K .......... .......... .......... .......... .......... 69% 23,2M 4s
176850K .......... .......... .......... .......... .......... 69% 17,2M 4s
176900K .......... .......... .......... .......... .......... 69% 47,9M 4s
176950K .......... .......... .......... .......... .......... 69% 32,2M 4s
177000K .......... .......... .......... .......... .......... 69% 23,3M 4s
177050K .......... .......... .......... .......... .......... 69% 65,7M 4s
177100K .......... .......... .......... .......... .......... 69% 15,5M 4s
177150K .......... .......... .......... .......... .......... 69% 38,0M 4s
177200K .......... .......... .......... .......... .......... 69% 36,7M 4s
177250K .......... .......... .......... .......... .......... 69% 37,9M 4s
177300K .......... .......... .......... .......... .......... 69% 14,6M 4s
177350K .......... .......... .......... .......... .......... 69% 31,0M 4s
177400K .......... .......... .......... .......... .......... 69% 29,3M 4s
177450K .......... .......... .......... .......... .......... 69% 27,7M 4s
177500K .......... .......... .......... .......... .......... 69% 42,7M 4s
177550K .......... .......... .......... .......... .......... 69% 26,6M 4s
177600K .......... .......... .......... .......... .......... 69% 70,7M 4s
177650K .......... .......... .......... .......... .......... 69% 28,4M 4s
177700K .......... .......... .......... .......... .......... 69% 15,3M 4s
177750K .......... .......... .......... .......... .......... 69% 40,9M 4s
177800K .......... .......... .......... .......... .......... 69% 29,3M 4s
177850K .......... .......... .......... .......... .......... 69% 34,6M 4s
177900K .......... .......... .......... .......... .......... 69% 37,1M 4s
177950K .......... .......... .......... .......... .......... 69% 7,03M 4s
178000K .......... .......... .......... .......... .......... 69%  115M 4s
178050K .......... .......... .......... .......... .......... 69% 78,3M 4s
178100K .......... .......... .......... .......... .......... 69% 29,5M 4s
178150K .......... .......... .......... .......... .......... 69% 12,6M 4s
178200K .......... .......... .......... .......... .......... 69% 38,2M 4s
178250K .......... .......... .......... .......... .......... 69% 37,0M 4s
178300K .......... .......... .......... .......... .......... 69% 1,31M 4s
178350K .......... .......... .......... .......... .......... 69% 13,8M 4s
178400K .......... .......... .......... .......... .......... 69% 53,3M 4s
178450K .......... .......... .......... .......... .......... 69%  283M 4s
178500K .......... .......... .......... .......... .......... 69%  954G 4s
178550K .......... .......... .......... .......... .......... 69%  382M 3s
178600K .......... .......... .......... .......... .......... 70%  383M 3s
178650K .......... .......... .......... .......... .......... 70%  132M 3s
178700K .......... .......... .......... .......... .......... 70%  295M 3s
178750K .......... .......... .......... .......... .......... 70%  954G 3s
178800K .......... .......... .......... .......... .......... 70%  176M 3s
178850K .......... .......... .......... .......... .......... 70% 12,1M 3s
178900K .......... .......... .......... .......... .......... 70%  954G 3s
178950K .......... .......... .......... .......... .......... 70%  285M 3s
179000K .......... .......... .......... .......... .......... 70%  383M 3s
179050K .......... .......... .......... .......... .......... 70%  174M 3s
179100K .......... .......... .......... .......... .......... 70%  954G 3s
179150K .......... .......... .......... .......... .......... 70%  168M 3s
179200K .......... .......... .......... .......... .......... 70%  265M 3s
179250K .......... .......... .......... .......... .......... 70%  422M 3s
179300K .......... .......... .......... .......... .......... 70%  247M 3s
179350K .......... .......... .......... .......... .......... 70%  954G 3s
179400K .......... .......... .......... .......... .......... 70%  324M 3s
179450K .......... .......... .......... .......... .......... 70%  325M 3s
179500K .......... .......... .......... .......... .......... 70% 15,7M 3s
179550K .......... .......... .......... .......... .......... 70% 13,0M 3s
179600K .......... .......... .......... .......... .......... 70% 37,2M 3s
179650K .......... .......... .......... .......... .......... 70% 35,9M 3s
179700K .......... .......... .......... .......... .......... 70% 35,7M 3s
179750K .......... .......... .......... .......... .......... 70% 36,7M 3s
179800K .......... .......... .......... .......... .......... 70% 36,3M 3s
179850K .......... .......... .......... .......... .......... 70% 35,8M 3s
179900K .......... .......... .......... .......... .......... 70% 28,6M 3s
179950K .......... .......... .......... .......... .......... 70% 29,6M 3s
180000K .......... .......... .......... .......... .......... 70% 11,1M 3s
180050K .......... .......... .......... .......... .......... 70% 29,7M 3s
180100K .......... .......... .......... .......... .......... 70% 39,0M 3s
180150K .......... .......... .......... .......... .......... 70% 18,7M 3s
180200K .......... .......... .......... .......... .......... 70% 4,86M 3s
180250K .......... .......... .......... .......... .......... 70% 55,1M 3s
180300K .......... .......... .......... .......... .......... 70% 12,8M 3s
180350K .......... .......... .......... .......... .......... 70% 28,8M 3s
180400K .......... .......... .......... .......... .......... 70% 31,0M 3s
180450K .......... .......... .......... .......... .......... 70% 13,5M 3s
180500K .......... .......... .......... .......... .......... 70% 21,6M 3s
180550K .......... .......... .......... .......... .......... 70% 35,7M 3s
180600K .......... .......... .......... .......... .......... 70% 27,4M 3s
180650K .......... .......... .......... .......... .......... 70% 35,4M 3s
180700K .......... .......... .......... .......... .......... 70% 36,5M 3s
180750K .......... .......... .......... .......... .......... 70% 27,7M 3s
180800K .......... .......... .......... .......... .......... 70% 40,5M 3s
180850K .......... .......... .......... .......... .......... 70% 18,5M 3s
180900K .......... .......... .......... .......... .......... 70% 25,2M 3s
180950K .......... .......... .......... .......... .......... 70% 46,1M 3s
181000K .......... .......... .......... .......... .......... 70% 38,0M 3s
181050K .......... .......... .......... .......... .......... 70% 26,1M 3s
181100K .......... .......... .......... .......... .......... 70% 5,44M 3s
181150K .......... .......... .......... .......... .......... 71%  149M 3s
181200K .......... .......... .......... .......... .......... 71%  131M 3s
181250K .......... .......... .......... .......... .......... 71%  139M 3s
181300K .......... .......... .......... .......... .......... 71%  136M 3s
181350K .......... .......... .......... .......... .......... 71% 96,5M 3s
181400K .......... .......... .......... .......... .......... 71%  142M 3s
181450K .......... .......... .......... .......... .......... 71% 13,1M 3s
181500K .......... .......... .......... .......... .......... 71%  167M 3s
181550K .......... .......... .......... .......... .......... 71%  103M 3s
181600K .......... .......... .......... .......... .......... 71% 17,8M 3s
181650K .......... .......... .......... .......... .......... 71% 18,5M 3s
181700K .......... .......... .......... .......... .......... 71% 30,0M 3s
181750K .......... .......... .......... .......... .......... 71% 38,0M 3s
181800K .......... .......... .......... .......... .......... 71% 28,8M 3s
181850K .......... .......... .......... .......... .......... 71% 29,5M 3s
181900K .......... .......... .......... .......... .......... 71% 55,3M 3s
181950K .......... .......... .......... .......... .......... 71% 29,6M 3s
182000K .......... .......... .......... .......... .......... 71% 46,2M 3s
182050K .......... .......... .......... .......... .......... 71% 15,3M 3s
182100K .......... .......... .......... .......... .......... 71% 38,3M 3s
182150K .......... .......... .......... .......... .......... 71% 25,1M 3s
182200K .......... .......... .......... .......... .......... 71% 34,5M 3s
182250K .......... .......... .......... .......... .......... 71% 36,5M 3s
182300K .......... .......... .......... .......... .......... 71% 29,9M 3s
182350K .......... .......... .......... .......... .......... 71% 27,4M 3s
182400K .......... .......... .......... .......... .......... 71% 18,9M 3s
182450K .......... .......... .......... .......... .......... 71% 17,8M 3s
182500K .......... .......... .......... .......... .......... 71% 18,1M 3s
182550K .......... .......... .......... .......... .......... 71% 29,9M 3s
182600K .......... .......... .......... .......... .......... 71% 52,5M 3s
182650K .......... .......... .......... .......... .......... 71% 33,3M 3s
182700K .......... .......... .......... .......... .......... 71% 28,9M 3s
182750K .......... .......... .......... .......... .......... 71% 35,2M 3s
182800K .......... .......... .......... .......... .......... 71% 32,6M 3s
182850K .......... .......... .......... .......... .......... 71% 39,1M 3s
182900K .......... .......... .......... .......... .......... 71% 13,4M 3s
182950K .......... .......... .......... .......... .......... 71% 30,8M 3s
183000K .......... .......... .......... .......... .......... 71% 24,2M 3s
183050K .......... .......... .......... .......... .......... 71% 42,1M 3s
183100K .......... .......... .......... .......... .......... 71% 35,3M 3s
183150K .......... .......... .......... .......... .......... 71% 7,07M 3s
183200K .......... .......... .......... .......... .......... 71%  287M 3s
183250K .......... .......... .......... .......... .......... 71% 20,5M 3s
183300K .......... .......... .......... .......... .......... 71% 30,1M 3s
183350K .......... .......... .......... .......... .......... 71% 31,1M 3s
183400K .......... .......... .......... .......... .......... 71% 35,2M 3s
183450K .......... .......... .......... .......... .......... 71% 15,5M 3s
183500K .......... .......... .......... .......... .......... 71% 31,4M 3s
183550K .......... .......... .......... .......... .......... 71% 37,2M 3s
183600K .......... .......... .......... .......... .......... 71% 35,9M 3s
183650K .......... .......... .......... .......... .......... 71% 37,5M 3s
183700K .......... .......... .......... .......... .......... 72% 37,3M 3s
183750K .......... .......... .......... .......... .......... 72% 15,7M 3s
183800K .......... .......... .......... .......... .......... 72% 24,4M 3s
183850K .......... .......... .......... .......... .......... 72% 1,51M 3s
183900K .......... .......... .......... .......... .......... 72% 15,7M 3s
183950K .......... .......... .......... .......... .......... 72% 41,0M 3s
184000K .......... .......... .......... .......... .......... 72% 20,0M 3s
184050K .......... .......... .......... .......... .......... 72% 43,4M 3s
184100K .......... .......... .......... .......... .......... 72%  954G 3s
184150K .......... .......... .......... .......... .......... 72% 35,5M 3s
184200K .......... .......... .......... .......... .......... 72% 43,5M 3s
184250K .......... .......... .......... .......... .......... 72% 91,1M 3s
184300K .......... .......... .......... .......... .......... 72% 68,2M 3s
184350K .......... .......... .......... .......... .......... 72%  124M 3s
184400K .......... .......... .......... .......... .......... 72%  274M 3s
184450K .......... .......... .......... .......... .......... 72%  140M 3s
184500K .......... .......... .......... .......... .......... 72%  954G 3s
184550K .......... .......... .......... .......... .......... 72%  266M 3s
184600K .......... .......... .......... .......... .......... 72%  307M 3s
184650K .......... .......... .......... .......... .......... 72%  217M 3s
184700K .......... .......... .......... .......... .......... 72%  954G 3s
184750K .......... .......... .......... .......... .......... 72%  153M 3s
184800K .......... .......... .......... .......... .......... 72%  232M 3s
184850K .......... .......... .......... .......... .......... 72%  243M 3s
184900K .......... .......... .......... .......... .......... 72%  162M 3s
184950K .......... .......... .......... .......... .......... 72%  954G 3s
185000K .......... .......... .......... .......... .......... 72%  149M 3s
185050K .......... .......... .......... .......... .......... 72%  101M 3s
185100K .......... .......... .......... .......... .......... 72%  129M 3s
185150K .......... .......... .......... .......... .......... 72% 22,5M 3s
185200K .......... .......... .......... .......... .......... 72% 17,1M 3s
185250K .......... .......... .......... .......... .......... 72% 17,1M 3s
185300K .......... .......... .......... .......... .......... 72% 32,6M 3s
185350K .......... .......... .......... .......... .......... 72% 36,9M 3s
185400K .......... .......... .......... .......... .......... 72% 39,2M 3s
185450K .......... .......... .......... .......... .......... 72% 29,3M 3s
185500K .......... .......... .......... .......... .......... 72% 20,0M 3s
185550K .......... .......... .......... .......... .......... 72% 34,3M 3s
185600K .......... .......... .......... .......... .......... 72% 27,5M 3s
185650K .......... .......... .......... .......... .......... 72% 58,2M 3s
185700K .......... .......... .......... .......... .......... 72% 4,05M 3s
185750K .......... .......... .......... .......... .......... 72% 16,5M 3s
185800K .......... .......... .......... .......... .......... 72% 31,4M 3s
185850K .......... .......... .......... .......... .......... 72% 15,3M 3s
185900K .......... .......... .......... .......... .......... 72% 36,3M 3s
185950K .......... .......... .......... .......... .......... 72% 32,1M 3s
186000K .......... .......... .......... .......... .......... 72% 32,8M 3s
186050K .......... .......... .......... .......... .......... 72% 31,7M 3s
186100K .......... .......... .......... .......... .......... 72% 21,3M 3s
186150K .......... .......... .......... .......... .......... 72% 32,3M 3s
186200K .......... .......... .......... .......... .......... 72% 40,3M 3s
186250K .......... .......... .......... .......... .......... 73% 25,2M 3s
186300K .......... .......... .......... .......... .......... 73% 18,0M 3s
186350K .......... .......... .......... .......... .......... 73% 32,2M 3s
186400K .......... .......... .......... .......... .......... 73% 18,9M 3s
186450K .......... .......... .......... .......... .......... 73% 29,3M 3s
186500K .......... .......... .......... .......... .......... 73% 38,9M 3s
186550K .......... .......... .......... .......... .......... 73% 26,3M 3s
186600K .......... .......... .......... .......... .......... 73% 37,8M 3s
186650K .......... .......... .......... .......... .......... 73% 15,6M 3s
186700K .......... .......... .......... .......... .......... 73% 14,5M 3s
186750K .......... .......... .......... .......... .......... 73% 39,3M 3s
186800K .......... .......... .......... .......... .......... 73% 43,1M 3s
186850K .......... .......... .......... .......... .......... 73% 31,4M 3s
186900K .......... .......... .......... .......... .......... 73% 39,3M 3s
186950K .......... .......... .......... .......... .......... 73% 29,2M 3s
187000K .......... .......... .......... .......... .......... 73% 36,1M 3s
187050K .......... .......... .......... .......... .......... 73% 11,8M 3s
187100K .......... .......... .......... .......... .......... 73% 33,0M 3s
187150K .......... .......... .......... .......... .......... 73% 24,8M 3s
187200K .......... .......... .......... .......... .......... 73% 56,3M 3s
187250K .......... .......... .......... .......... .......... 73% 48,8M 3s
187300K .......... .......... .......... .......... .......... 73% 37,7M 3s
187350K .......... .......... .......... .......... .......... 73% 13,1M 3s
187400K .......... .......... .......... .......... .......... 73% 40,8M 3s
187450K .......... .......... .......... .......... .......... 73% 18,7M 3s
187500K .......... .......... .......... .......... .......... 73% 38,6M 3s
187550K .......... .......... .......... .......... .......... 73% 34,7M 3s
187600K .......... .......... .......... .......... .......... 73% 37,0M 3s
187650K .......... .......... .......... .......... .......... 73% 32,3M 3s
187700K .......... .......... .......... .......... .......... 73% 47,9M 3s
187750K .......... .......... .......... .......... .......... 73% 16,1M 3s
187800K .......... .......... .......... .......... .......... 73% 32,5M 3s
187850K .......... .......... .......... .......... .......... 73% 26,4M 3s
187900K .......... .......... .......... .......... .......... 73% 17,9M 3s
187950K .......... .......... .......... .......... .......... 73% 28,3M 3s
188000K .......... .......... .......... .......... .......... 73% 37,5M 3s
188050K .......... .......... .......... .......... .......... 73% 30,6M 3s
188100K .......... .......... .......... .......... .......... 73% 27,4M 3s
188150K .......... .......... .......... .......... .......... 73% 36,2M 3s
188200K .......... .......... .......... .......... .......... 73% 26,7M 3s
188250K .......... .......... .......... .......... .......... 73% 30,2M 3s
188300K .......... .......... .......... .......... .......... 73% 18,3M 3s
188350K .......... .......... .......... .......... .......... 73% 67,9M 3s
188400K .......... .......... .......... .......... .......... 73% 16,0M 3s
188450K .......... .......... .......... .......... .......... 73% 63,0M 3s
188500K .......... .......... .......... .......... .......... 73% 20,8M 3s
188550K .......... .......... .......... .......... .......... 73% 17,5M 3s
188600K .......... .......... .......... .......... .......... 73% 44,8M 3s
188650K .......... .......... .......... .......... .......... 73% 34,0M 3s
188700K .......... .......... .......... .......... .......... 73% 37,7M 3s
188750K .......... .......... .......... .......... .......... 73% 31,6M 3s
188800K .......... .......... .......... .......... .......... 74% 25,4M 3s
188850K .......... .......... .......... .......... .......... 74% 34,4M 3s
188900K .......... .......... .......... .......... .......... 74% 18,2M 3s
188950K .......... .......... .......... .......... .......... 74% 21,6M 3s
189000K .......... .......... .......... .......... .......... 74% 27,8M 3s
189050K .......... .......... .......... .......... .......... 74% 37,0M 3s
189100K .......... .......... .......... .......... .......... 74% 36,8M 3s
189150K .......... .......... .......... .......... .......... 74% 32,8M 3s
189200K .......... .......... .......... .......... .......... 74% 31,1M 3s
189250K .......... .......... .......... .......... .......... 74% 36,8M 3s
189300K .......... .......... .......... .......... .......... 74% 16,9M 3s
189350K .......... .......... .......... .......... .......... 74% 17,2M 3s
189400K .......... .......... .......... .......... .......... 74% 29,1M 3s
189450K .......... .......... .......... .......... .......... 74% 35,6M 3s
189500K .......... .......... .......... .......... .......... 74% 30,2M 3s
189550K .......... .......... .......... .......... .......... 74% 30,0M 3s
189600K .......... .......... .......... .......... .......... 74% 30,8M 3s
189650K .......... .......... .......... .......... .......... 74% 1,14M 3s
189700K .......... .......... .......... .......... .......... 74%  954G 3s
189750K .......... .......... .......... .......... .......... 74%  252M 3s
189800K .......... .......... .......... .......... .......... 74%  194M 3s
189850K .......... .......... .......... .......... .......... 74%  398M 3s
189900K .......... .......... .......... .......... .......... 74%  425M 3s
189950K .......... .......... .......... .......... .......... 74%  954G 3s
190000K .......... .......... .......... .......... .......... 74%  387M 3s
190050K .......... .......... .......... .......... .......... 74%  368M 3s
190100K .......... .......... .......... .......... .......... 74%  375M 3s
190150K .......... .......... .......... .......... .......... 74%  954G 3s
190200K .......... .......... .......... .......... .......... 74%  365M 3s
190250K .......... .......... .......... .......... .......... 74%  371M 3s
190300K .......... .......... .......... .......... .......... 74%  381M 3s
190350K .......... .......... .......... .......... .......... 74%  406M 3s
190400K .......... .......... .......... .......... .......... 74%  954G 3s
190450K .......... .......... .......... .......... .......... 74% 1,45M 3s
190500K .......... .......... .......... .......... .......... 74% 5,51M 3s
190550K .......... .......... .......... .......... .......... 74% 65,9M 3s
190600K .......... .......... .......... .......... .......... 74% 71,3M 3s
190650K .......... .......... .......... .......... .......... 74%  295M 3s
190700K .......... .......... .......... .......... .......... 74%  954G 3s
190750K .......... .......... .......... .......... .......... 74% 16,0M 3s
190800K .......... .......... .......... .......... .......... 74% 73,1M 3s
190850K .......... .......... .......... .......... .......... 74% 7,52M 3s
190900K .......... .......... .......... .......... .......... 74%  159M 3s
190950K .......... .......... .......... .......... .......... 74% 70,6M 3s
191000K .......... .......... .......... .......... .......... 74%  954G 3s
191050K .......... .......... .......... .......... .......... 74% 72,9M 3s
191100K .......... .......... .......... .......... .......... 74%  208M 3s
191150K .......... .......... .......... .......... .......... 74%  124M 3s
191200K .......... .......... .......... .......... .......... 74%  173M 3s
191250K .......... .......... .......... .......... .......... 74%  954G 3s
191300K .......... .......... .......... .......... .......... 74%  309M 3s
191350K .......... .......... .......... .......... .......... 75%  370M 3s
191400K .......... .......... .......... .......... .......... 75% 93,3M 3s
191450K .......... .......... .......... .......... .......... 75%  954G 3s
191500K .......... .......... .......... .......... .......... 75%  203M 3s
191550K .......... .......... .......... .......... .......... 75%  371M 3s
191600K .......... .......... .......... .......... .......... 75%  383M 3s
191650K .......... .......... .......... .......... .......... 75%  167M 3s
191700K .......... .......... .......... .......... .......... 75%  954G 3s
191750K .......... .......... .......... .......... .......... 75%  184M 3s
191800K .......... .......... .......... .......... .......... 75%  173M 3s
191850K .......... .......... .......... .......... .......... 75%  214M 3s
191900K .......... .......... .......... .......... .......... 75%  224M 3s
191950K .......... .......... .......... .......... .......... 75%  954G 3s
192000K .......... .......... .......... .......... .......... 75% 96,3M 3s
192050K .......... .......... .......... .......... .......... 75% 44,7M 3s
192100K .......... .......... .......... .......... .......... 75%  248M 3s
192150K .......... .......... .......... .......... .......... 75%  954G 3s
192200K .......... .......... .......... .......... .......... 75% 30,6M 3s
192250K .......... .......... .......... .......... .......... 75% 12,6M 3s
192300K .......... .......... .......... .......... .......... 75% 35,5M 3s
192350K .......... .......... .......... .......... .......... 75% 24,7M 3s
192400K .......... .......... .......... .......... .......... 75% 52,7M 3s
192450K .......... .......... .......... .......... .......... 75% 36,0M 3s
192500K .......... .......... .......... .......... .......... 75% 30,0M 3s
192550K .......... .......... .......... .......... .......... 75% 48,4M 3s
192600K .......... .......... .......... .......... .......... 75% 27,1M 3s
192650K .......... .......... .......... .......... .......... 75% 35,4M 3s
192700K .......... .......... .......... .......... .......... 75% 15,9M 3s
192750K .......... .......... .......... .......... .......... 75% 35,3M 3s
192800K .......... .......... .......... .......... .......... 75% 32,4M 3s
192850K .......... .......... .......... .......... .......... 75% 41,1M 3s
192900K .......... .......... .......... .......... .......... 75% 32,5M 3s
192950K .......... .......... .......... .......... .......... 75% 27,8M 3s
193000K .......... .......... .......... .......... .......... 75% 30,4M 3s
193050K .......... .......... .......... .......... .......... 75% 37,7M 3s
193100K .......... .......... .......... .......... .......... 75% 16,5M 3s
193150K .......... .......... .......... .......... .......... 75% 12,5M 3s
193200K .......... .......... .......... .......... .......... 75%  216M 3s
193250K .......... .......... .......... .......... .......... 75%  105M 3s
193300K .......... .......... .......... .......... .......... 75% 49,9M 3s
193350K .......... .......... .......... .......... .......... 75% 8,70M 3s
193400K .......... .......... .......... .......... .......... 75% 78,0M 3s
193450K .......... .......... .......... .......... .......... 75%  150M 3s
193500K .......... .......... .......... .......... .......... 75% 40,2M 3s
193550K .......... .......... .......... .......... .......... 75% 46,5M 3s
193600K .......... .......... .......... .......... .......... 75% 39,9M 3s
193650K .......... .......... .......... .......... .......... 75% 43,9M 3s
193700K .......... .......... .......... .......... .......... 75% 30,5M 3s
193750K .......... .......... .......... .......... .......... 75% 35,4M 3s
193800K .......... .......... .......... .......... .......... 75% 8,32M 3s
193850K .......... .......... .......... .......... .......... 75%  105M 3s
193900K .......... .......... .......... .......... .......... 76% 14,1M 3s
193950K .......... .......... .......... .......... .......... 76% 80,6M 3s
194000K .......... .......... .......... .......... .......... 76% 9,04M 3s
194050K .......... .......... .......... .......... .......... 76% 48,5M 3s
194100K .......... .......... .......... .......... .......... 76% 95,7M 3s
194150K .......... .......... .......... .......... .......... 76%  103M 3s
194200K .......... .......... .......... .......... .......... 76% 94,1M 3s
194250K .......... .......... .......... .......... .......... 76% 47,4M 3s
194300K .......... .......... .......... .......... .......... 76% 30,8M 3s
194350K .......... .......... .......... .......... .......... 76% 32,3M 3s
194400K .......... .......... .......... .......... .......... 76% 41,4M 3s
194450K .......... .......... .......... .......... .......... 76% 24,0M 3s
194500K .......... .......... .......... .......... .......... 76% 7,99M 3s
194550K .......... .......... .......... .......... .......... 76% 51,9M 3s
194600K .......... .......... .......... .......... .......... 76%  202M 3s
194650K .......... .......... .......... .......... .......... 76%  244M 3s
194700K .......... .......... .......... .......... .......... 76% 80,1M 3s
194750K .......... .......... .......... .......... .......... 76% 64,8M 3s
194800K .......... .......... .......... .......... .......... 76% 23,3M 3s
194850K .......... .......... .......... .......... .......... 76% 17,6M 3s
194900K .......... .......... .......... .......... .......... 76% 82,6M 3s
194950K .......... .......... .......... .......... .......... 76% 18,7M 3s
195000K .......... .......... .......... .......... .......... 76% 17,3M 3s
195050K .......... .......... .......... .......... .......... 76% 81,2M 3s
195100K .......... .......... .......... .......... .......... 76% 64,8M 3s
195150K .......... .......... .......... .......... .......... 76% 5,62M 3s
195200K .......... .......... .......... .......... .......... 76% 77,1M 3s
195250K .......... .......... .......... .......... .......... 76%  138M 3s
195300K .......... .......... .......... .......... .......... 76% 82,1M 3s
195350K .......... .......... .......... .......... .......... 76% 56,8M 3s
195400K .......... .......... .......... .......... .......... 76% 95,5M 3s
195450K .......... .......... .......... .......... .......... 76% 55,2M 3s
195500K .......... .......... .......... .......... .......... 76% 41,6M 3s
195550K .......... .......... .......... .......... .......... 76% 15,3M 3s
195600K .......... .......... .......... .......... .......... 76% 29,5M 3s
195650K .......... .......... .......... .......... .......... 76% 60,5M 3s
195700K .......... .......... .......... .......... .......... 76% 33,3M 3s
195750K .......... .......... .......... .......... .......... 76% 17,1M 3s
195800K .......... .......... .......... .......... .......... 76% 23,3M 3s
195850K .......... .......... .......... .......... .......... 76% 38,5M 3s
195900K .......... .......... .......... .......... .......... 76% 43,1M 3s
195950K .......... .......... .......... .......... .......... 76% 39,3M 3s
196000K .......... .......... .......... .......... .......... 76% 5,68M 3s
196050K .......... .......... .......... .......... .......... 76%  112M 3s
196100K .......... .......... .......... .......... .......... 76% 98,7M 3s
196150K .......... .......... .......... .......... .......... 76% 95,1M 3s
196200K .......... .......... .......... .......... .......... 76% 71,3M 3s
196250K .......... .......... .......... .......... .......... 76% 58,6M 3s
196300K .......... .......... .......... .......... .......... 76% 15,3M 3s
196350K .......... .......... .......... .......... .......... 76% 58,1M 3s
196400K .......... .......... .......... .......... .......... 76%  143M 3s
196450K .......... .......... .......... .......... .......... 77%  134M 3s
196500K .......... .......... .......... .......... .......... 77% 40,3M 3s
196550K .......... .......... .......... .......... .......... 77% 32,5M 3s
196600K .......... .......... .......... .......... .......... 77% 34,1M 3s
196650K .......... .......... .......... .......... .......... 77% 19,9M 3s
196700K .......... .......... .......... .......... .......... 77% 5,16M 3s
196750K .......... .......... .......... .......... .......... 77%  108M 3s
196800K .......... .......... .......... .......... .......... 77%  121M 3s
196850K .......... .......... .......... .......... .......... 77%  111M 3s
196900K .......... .......... .......... .......... .......... 77% 73,4M 3s
196950K .......... .......... .......... .......... .......... 77% 5,56M 3s
197000K .......... .......... .......... .......... .......... 77% 93,9M 3s
197050K .......... .......... .......... .......... .......... 77%  118M 3s
197100K .......... .......... .......... .......... .......... 77%  112M 3s
197150K .......... .......... .......... .......... .......... 77% 89,2M 3s
197200K .......... .......... .......... .......... .......... 77% 72,8M 3s
197250K .......... .......... .......... .......... .......... 77% 84,2M 3s
197300K .......... .......... .......... .......... .......... 77% 56,6M 3s
197350K .......... .......... .......... .......... .......... 77%  100M 3s
197400K .......... .......... .......... .......... .......... 77% 72,2M 3s
197450K .......... .......... .......... .......... .......... 77% 45,4M 3s
197500K .......... .......... .......... .......... .......... 77% 21,0M 3s
197550K .......... .......... .......... .......... .......... 77% 29,4M 3s
197600K .......... .......... .......... .......... .......... 77% 34,1M 3s
197650K .......... .......... .......... .......... .......... 77% 37,6M 3s
197700K .......... .......... .......... .......... .......... 77% 37,2M 3s
197750K .......... .......... .......... .......... .......... 77% 38,1M 3s
197800K .......... .......... .......... .......... .......... 77% 27,2M 3s
197850K .......... .......... .......... .......... .......... 77% 28,9M 3s
197900K .......... .......... .......... .......... .......... 77% 15,4M 3s
197950K .......... .......... .......... .......... .......... 77% 35,8M 3s
198000K .......... .......... .......... .......... .......... 77% 29,8M 3s
198050K .......... .......... .......... .......... .......... 77% 34,0M 3s
198100K .......... .......... .......... .......... .......... 77% 38,9M 3s
198150K .......... .......... .......... .......... .......... 77% 36,5M 3s
198200K .......... .......... .......... .......... .......... 77% 37,9M 3s
198250K .......... .......... .......... .......... .......... 77% 34,7M 3s
198300K .......... .......... .......... .......... .......... 77% 17,5M 3s
198350K .......... .......... .......... .......... .......... 77% 58,7M 3s
198400K .......... .......... .......... .......... .......... 77% 20,0M 3s
198450K .......... .......... .......... .......... .......... 77% 35,3M 3s
198500K .......... .......... .......... .......... .......... 77% 30,6M 3s
198550K .......... .......... .......... .......... .......... 77% 16,1M 3s
198600K .......... .......... .......... .......... .......... 77% 36,8M 3s
198650K .......... .......... .......... .......... .......... 77% 40,2M 3s
198700K .......... .......... .......... .......... .......... 77% 30,2M 3s
198750K .......... .......... .......... .......... .......... 77% 10,3M 3s
198800K .......... .......... .......... .......... .......... 77% 44,2M 3s
198850K .......... .......... .......... .......... .......... 77% 27,2M 3s
198900K .......... .......... .......... .......... .......... 77% 34,6M 3s
198950K .......... .......... .......... .......... .......... 77% 16,7M 3s
199000K .......... .......... .......... .......... .......... 78% 36,4M 3s
199050K .......... .......... .......... .......... .......... 78% 10,5M 3s
199100K .......... .......... .......... .......... .......... 78%  150M 3s
199150K .......... .......... .......... .......... .......... 78%  268K 3s
199200K .......... .......... .......... .......... .......... 78% 73,7M 3s
199250K .......... .......... .......... .......... .......... 78% 33,7M 3s
199300K .......... .......... .......... .......... .......... 78% 29,6M 3s
199350K .......... .......... .......... .......... .......... 78% 27,2M 3s
199400K .......... .......... .......... .......... .......... 78% 31,6M 3s
199450K .......... .......... .......... .......... .......... 78% 15,4M 3s
199500K .......... .......... .......... .......... .......... 78% 37,3M 3s
199550K .......... .......... .......... .......... .......... 78% 2,21M 3s
199600K .......... .......... .......... .......... .......... 78% 4,42M 3s
199650K .......... .......... .......... .......... .......... 78% 28,9M 3s
199700K .......... .......... .......... .......... .......... 78% 22,5M 3s
199750K .......... .......... .......... .......... .......... 78% 22,6M 3s
199800K .......... .......... .......... .......... .......... 78% 9,75M 3s
199850K .......... .......... .......... .......... .......... 78% 40,1M 3s
199900K .......... .......... .......... .......... .......... 78% 35,6M 3s
199950K .......... .......... .......... .......... .......... 78% 27,3M 3s
200000K .......... .......... .......... .......... .......... 78% 24,4M 3s
200050K .......... .......... .......... .......... .......... 78% 26,0M 3s
200100K .......... .......... .......... .......... .......... 78% 17,6M 3s
200150K .......... .......... .......... .......... .......... 78% 20,7M 3s
200200K .......... .......... .......... .......... .......... 78% 26,6M 3s
200250K .......... .......... .......... .......... .......... 78% 40,9M 3s
200300K .......... .......... .......... .......... .......... 78% 53,2M 3s
200350K .......... .......... .......... .......... .......... 78%  135M 3s
200400K .......... .......... .......... .......... .......... 78%  357M 3s
200450K .......... .......... .......... .......... .......... 78%  954G 2s
200500K .......... .......... .......... .......... .......... 78%  358M 2s
200550K .......... .......... .......... .......... .......... 78%  401M 2s
200600K .......... .......... .......... .......... .......... 78%  396M 2s
200650K .......... .......... .......... .......... .......... 78%  234M 2s
200700K .......... .......... .......... .......... .......... 78%  954G 2s
200750K .......... .......... .......... .......... .......... 78%  144M 2s
200800K .......... .......... .......... .......... .......... 78%  351M 2s
200850K .......... .......... .......... .......... .......... 78%  416M 2s
200900K .......... .......... .......... .......... .......... 78% 25,6M 2s
200950K .......... .......... .......... .......... .......... 78% 15,7M 2s
201000K .......... .......... .......... .......... .......... 78% 29,0M 2s
201050K .......... .......... .......... .......... .......... 78% 27,7M 2s
201100K .......... .......... .......... .......... .......... 78% 14,0M 2s
201150K .......... .......... .......... .......... .......... 78% 39,0M 2s
201200K .......... .......... .......... .......... .......... 78% 40,4M 2s
201250K .......... .......... .......... .......... .......... 78% 26,4M 2s
201300K .......... .......... .......... .......... .......... 78% 15,4M 2s
201350K .......... .......... .......... .......... .......... 78% 25,1M 2s
201400K .......... .......... .......... .......... .......... 78% 27,1M 2s
201450K .......... .......... .......... .......... .......... 78% 39,0M 2s
201500K .......... .......... .......... .......... .......... 78% 66,6M 2s
201550K .......... .......... .......... .......... .......... 79% 23,3M 2s
201600K .......... .......... .......... .......... .......... 79% 75,7M 2s
201650K .......... .......... .......... .......... .......... 79% 21,9M 2s
201700K .......... .......... .......... .......... .......... 79% 23,6M 2s
201750K .......... .......... .......... .......... .......... 79% 18,4M 2s
201800K .......... .......... .......... .......... .......... 79% 29,4M 2s
201850K .......... .......... .......... .......... .......... 79% 39,9M 2s
201900K .......... .......... .......... .......... .......... 79% 24,5M 2s
201950K .......... .......... .......... .......... .......... 79% 39,9M 2s
202000K .......... .......... .......... .......... .......... 79% 33,5M 2s
202050K .......... .......... .......... .......... .......... 79% 34,3M 2s
202100K .......... .......... .......... .......... .......... 79% 29,4M 2s
202150K .......... .......... .......... .......... .......... 79% 16,9M 2s
202200K .......... .......... .......... .......... .......... 79% 35,0M 2s
202250K .......... .......... .......... .......... .......... 79% 29,9M 2s
202300K .......... .......... .......... .......... .......... 79% 18,8M 2s
202350K .......... .......... .......... .......... .......... 79% 29,6M 2s
202400K .......... .......... .......... .......... .......... 79% 24,2M 2s
202450K .......... .......... .......... .......... .......... 79% 75,0M 2s
202500K .......... .......... .......... .......... .......... 79% 35,3M 2s
202550K .......... .......... .......... .......... .......... 79% 11,9M 2s
202600K .......... .......... .......... .......... .......... 79% 29,1M 2s
202650K .......... .......... .......... .......... .......... 79% 23,3M 2s
202700K .......... .......... .......... .......... .......... 79% 32,5M 2s
202750K .......... .......... .......... .......... .......... 79% 28,5M 2s
202800K .......... .......... .......... .......... .......... 79% 33,3M 2s
202850K .......... .......... .......... .......... .......... 79% 24,0M 2s
202900K .......... .......... .......... .......... .......... 79% 59,7M 2s
202950K .......... .......... .......... .......... .......... 79% 31,3M 2s
203000K .......... .......... .......... .......... .......... 79% 15,4M 2s
203050K .......... .......... .......... .......... .......... 79% 26,0M 2s
203100K .......... .......... .......... .......... .......... 79% 33,9M 2s
203150K .......... .......... .......... .......... .......... 79% 1,15M 2s
203200K .......... .......... .......... .......... .......... 79%  209M 2s
203250K .......... .......... .......... .......... .......... 79%  192M 2s
203300K .......... .......... .......... .......... .......... 79%  163M 2s
203350K .......... .......... .......... .......... .......... 79% 5,23M 2s
203400K .......... .......... .......... .......... .......... 79%  954G 2s
203450K .......... .......... .......... .......... .......... 79% 23,5M 2s
203500K .......... .......... .......... .......... .......... 79%  315M 2s
203550K .......... .......... .......... .......... .......... 79% 81,0M 2s
203600K .......... .......... .......... .......... .......... 79%  161M 2s
203650K .......... .......... .......... .......... .......... 79%  369M 2s
203700K .......... .......... .......... .......... .......... 79%  127M 2s
203750K .......... .......... .......... .......... .......... 79%  250M 2s
203800K .......... .......... .......... .......... .......... 79%  197M 2s
203850K .......... .......... .......... .......... .......... 79%  345M 2s
203900K .......... .......... .......... .......... .......... 79%  954G 2s
203950K .......... .......... .......... .......... .......... 79%  329M 2s
204000K .......... .......... .......... .......... .......... 79% 10,7M 2s
204050K .......... .......... .......... .......... .......... 79% 21,2M 2s
204100K .......... .......... .......... .......... .......... 80%  954G 2s
204150K .......... .......... .......... .......... .......... 80%  123M 2s
204200K .......... .......... .......... .......... .......... 80%  320M 2s
204250K .......... .......... .......... .......... .......... 80%  407M 2s
204300K .......... .......... .......... .......... .......... 80%  954G 2s
204350K .......... .......... .......... .......... .......... 80%  378M 2s
204400K .......... .......... .......... .......... .......... 80%  114M 2s
204450K .......... .......... .......... .......... .......... 80%  154M 2s
204500K .......... .......... .......... .......... .......... 80%  209M 2s
204550K .......... .......... .......... .......... .......... 80%  954G 2s
204600K .......... .......... .......... .......... .......... 80%  167M 2s
204650K .......... .......... .......... .......... .......... 80%  237M 2s
204700K .......... .......... .......... .......... .......... 80%  348M 2s
204750K .......... .......... .......... .......... .......... 80%  368M 2s
204800K .......... .......... .......... .......... .......... 80%  954G 2s
204850K .......... .......... .......... .......... .......... 80%  104M 2s
204900K .......... .......... .......... .......... .......... 80% 34,4M 2s
204950K .......... .......... .......... .......... .......... 80% 40,9M 2s
205000K .......... .......... .......... .......... .......... 80% 16,5M 2s
205050K .......... .......... .......... .......... .......... 80% 36,2M 2s
205100K .......... .......... .......... .......... .......... 80% 42,9M 2s
205150K .......... .......... .......... .......... .......... 80% 25,2M 2s
205200K .......... .......... .......... .......... .......... 80% 11,4M 2s
205250K .......... .......... .......... .......... .......... 80% 7,56M 2s
205300K .......... .......... .......... .......... .......... 80% 18,5M 2s
205350K .......... .......... .......... .......... .......... 80% 48,1M 2s
205400K .......... .......... .......... .......... .......... 80% 23,1M 2s
205450K .......... .......... .......... .......... .......... 80% 27,4M 2s
205500K .......... .......... .......... .......... .......... 80% 50,6M 2s
205550K .......... .......... .......... .......... .......... 80% 24,8M 2s
205600K .......... .......... .......... .......... .......... 80% 32,9M 2s
205650K .......... .......... .......... .......... .......... 80% 11,4M 2s
205700K .......... .......... .......... .......... .......... 80% 31,4M 2s
205750K .......... .......... .......... .......... .......... 80% 24,3M 2s
205800K .......... .......... .......... .......... .......... 80% 44,2M 2s
205850K .......... .......... .......... .......... .......... 80% 16,3M 2s
205900K .......... .......... .......... .......... .......... 80% 30,7M 2s
205950K .......... .......... .......... .......... .......... 80% 43,3M 2s
206000K .......... .......... .......... .......... .......... 80% 29,2M 2s
206050K .......... .......... .......... .......... .......... 80% 19,8M 2s
206100K .......... .......... .......... .......... .......... 80% 35,4M 2s
206150K .......... .......... .......... .......... .......... 80% 37,4M 2s
206200K .......... .......... .......... .......... .......... 80% 30,3M 2s
206250K .......... .......... .......... .......... .......... 80% 44,2M 2s
206300K .......... .......... .......... .......... .......... 80% 20,7M 2s
206350K .......... .......... .......... .......... .......... 80% 31,9M 2s
206400K .......... .......... .......... .......... .......... 80% 33,9M 2s
206450K .......... .......... .......... .......... .......... 80% 18,3M 2s
206500K .......... .......... .......... .......... .......... 80% 26,3M 2s
206550K .......... .......... .......... .......... .......... 80% 34,5M 2s
206600K .......... .......... .......... .......... .......... 80% 32,6M 2s
206650K .......... .......... .......... .......... .......... 81% 27,7M 2s
206700K .......... .......... .......... .......... .......... 81% 21,4M 2s
206750K .......... .......... .......... .......... .......... 81% 36,9M 2s
206800K .......... .......... .......... .......... .......... 81% 36,9M 2s
206850K .......... .......... .......... .......... .......... 81% 34,3M 2s
206900K .......... .......... .......... .......... .......... 81% 16,2M 2s
206950K .......... .......... .......... .......... .......... 81% 38,6M 2s
207000K .......... .......... .......... .......... .......... 81% 30,5M 2s
207050K .......... .......... .......... .......... .......... 81% 33,9M 2s
207100K .......... .......... .......... .......... .......... 81% 30,5M 2s
207150K .......... .......... .......... .......... .......... 81% 34,9M 2s
207200K .......... .......... .......... .......... .......... 81% 28,8M 2s
207250K .......... .......... .......... .......... .......... 81% 28,0M 2s
207300K .......... .......... .......... .......... .......... 81% 31,8M 2s
207350K .......... .......... .......... .......... .......... 81% 19,0M 2s
207400K .......... .......... .......... .......... .......... 81% 22,0M 2s
207450K .......... .......... .......... .......... .......... 81% 19,8M 2s
207500K .......... .......... .......... .......... .......... 81% 21,4M 2s
207550K .......... .......... .......... .......... .......... 81%  954G 2s
207600K .......... .......... .......... .......... .......... 81% 29,2M 2s
207650K .......... .......... .......... .......... .......... 81% 23,4M 2s
207700K .......... .......... .......... .......... .......... 81% 29,5M 2s
207750K .......... .......... .......... .......... .......... 81%  954G 2s
207800K .......... .......... .......... .......... .......... 81% 24,0M 2s
207850K .......... .......... .......... .......... .......... 81% 30,7M 2s
207900K .......... .......... .......... .......... .......... 81% 49,9M 2s
207950K .......... .......... .......... .......... .......... 81% 24,5M 2s
208000K .......... .......... .......... .......... .......... 81% 30,9M 2s
208050K .......... .......... .......... .......... .......... 81% 26,7M 2s
208100K .......... .......... .......... .......... .......... 81% 25,8M 2s
208150K .......... .......... .......... .......... .......... 81% 20,4M 2s
208200K .......... .......... .......... .......... .......... 81% 27,8M 2s
208250K .......... .......... .......... .......... .......... 81% 27,0M 2s
208300K .......... .......... .......... .......... .......... 81% 16,5M 2s
208350K .......... .......... .......... .......... .......... 81% 30,4M 2s
208400K .......... .......... .......... .......... .......... 81% 28,9M 2s
208450K .......... .......... .......... .......... .......... 81% 29,5M 2s
208500K .......... .......... .......... .......... .......... 81% 29,4M 2s
208550K .......... .......... .......... .......... .......... 81% 38,5M 2s
208600K .......... .......... .......... .......... .......... 81% 19,2M 2s
208650K .......... .......... .......... .......... .......... 81% 32,6M 2s
208700K .......... .......... .......... .......... .......... 81% 19,0M 2s
208750K .......... .......... .......... .......... .......... 81%  954G 2s
208800K .......... .......... .......... .......... .......... 81% 60,8M 2s
208850K .......... .......... .......... .......... .......... 81% 29,3M 2s
208900K .......... .......... .......... .......... .......... 81% 36,3M 2s
208950K .......... .......... .......... .......... .......... 81% 17,4M 2s
209000K .......... .......... .......... .......... .......... 81% 37,6M 2s
209050K .......... .......... .......... .......... .......... 81% 15,8M 2s
209100K .......... .......... .......... .......... .......... 81% 37,3M 2s
209150K .......... .......... .......... .......... .......... 81% 29,6M 2s
209200K .......... .......... .......... .......... .......... 82% 43,5M 2s
209250K .......... .......... .......... .......... .......... 82% 43,5M 2s
209300K .......... .......... .......... .......... .......... 82% 39,8M 2s
209350K .......... .......... .......... .......... .......... 82% 26,5M 2s
209400K .......... .......... .......... .......... .......... 82% 31,4M 2s
209450K .......... .......... .......... .......... .......... 82% 36,3M 2s
209500K .......... .......... .......... .......... .......... 82% 14,9M 2s
209550K .......... .......... .......... .......... .......... 82% 31,2M 2s
209600K .......... .......... .......... .......... .......... 82% 25,3M 2s
209650K .......... .......... .......... .......... .......... 82% 19,3M 2s
209700K .......... .......... .......... .......... .......... 82% 30,4M 2s
209750K .......... .......... .......... .......... .......... 82% 25,8M 2s
209800K .......... .......... .......... .......... .......... 82% 36,2M 2s
209850K .......... .......... .......... .......... .......... 82% 59,6M 2s
209900K .......... .......... .......... .......... .......... 82% 20,9M 2s
209950K .......... .......... .......... .......... .......... 82% 35,3M 2s
210000K .......... .......... .......... .......... .......... 82% 37,8M 2s
210050K .......... .......... .......... .......... .......... 82% 35,3M 2s
210100K .......... .......... .......... .......... .......... 82% 38,2M 2s
210150K .......... .......... .......... .......... .......... 82% 31,3M 2s
210200K .......... .......... .......... .......... .......... 82% 26,4M 2s
210250K .......... .......... .......... .......... .......... 82% 33,0M 2s
210300K .......... .......... .......... .......... .......... 82% 18,5M 2s
210350K .......... .......... .......... .......... .......... 82% 36,2M 2s
210400K .......... .......... .......... .......... .......... 82% 21,9M 2s
210450K .......... .......... .......... .......... .......... 82% 25,2M 2s
210500K .......... .......... .......... .......... .......... 82% 32,6M 2s
210550K .......... .......... .......... .......... .......... 82% 35,8M 2s
210600K .......... .......... .......... .......... .......... 82% 30,8M 2s
210650K .......... .......... .......... .......... .......... 82% 26,9M 2s
210700K .......... .......... .......... .......... .......... 82% 41,8M 2s
210750K .......... .......... .......... .......... .......... 82% 16,4M 2s
210800K .......... .......... .......... .......... .......... 82% 28,4M 2s
210850K .......... .......... .......... .......... .......... 82% 21,6M 2s
210900K .......... .......... .......... .......... .......... 82% 30,9M 2s
210950K .......... .......... .......... .......... .......... 82% 35,8M 2s
211000K .......... .......... .......... .......... .......... 82% 26,2M 2s
211050K .......... .......... .......... .......... .......... 82% 60,7M 2s
211100K .......... .......... .......... .......... .......... 82% 25,6M 2s
211150K .......... .......... .......... .......... .......... 82% 11,1M 2s
211200K .......... .......... .......... .......... .......... 82% 89,2M 2s
211250K .......... .......... .......... .......... .......... 82% 27,3M 2s
211300K .......... .......... .......... .......... .......... 82% 35,0M 2s
211350K .......... .......... .......... .......... .......... 82% 14,0M 2s
211400K .......... .......... .......... .......... .......... 82% 34,7M 2s
211450K .......... .......... .......... .......... .......... 82% 42,3M 2s
211500K .......... .......... .......... .......... .......... 82%  998K 2s
211550K .......... .......... .......... .......... .......... 82%  954G 2s
211600K .......... .......... .......... .......... .......... 82% 39,5M 2s
211650K .......... .......... .......... .......... .......... 82% 29,3M 2s
211700K .......... .......... .......... .......... .......... 82% 77,7M 2s
211750K .......... .......... .......... .......... .......... 83% 14,2M 2s
211800K .......... .......... .......... .......... .......... 83%  118M 2s
211850K .......... .......... .......... .......... .......... 83% 15,9M 2s
211900K .......... .......... .......... .......... .......... 83%  329M 2s
211950K .......... .......... .......... .......... .......... 83% 10,3M 2s
212000K .......... .......... .......... .......... .......... 83% 30,6M 2s
212050K .......... .......... .......... .......... .......... 83% 19,1M 2s
212100K .......... .......... .......... .......... .......... 83%  954G 2s
212150K .......... .......... .......... .......... .......... 83%  157M 2s
212200K .......... .......... .......... .......... .......... 83%  237M 2s
212250K .......... .......... .......... .......... .......... 83%  283M 2s
212300K .......... .......... .......... .......... .......... 83%  300M 2s
212350K .......... .......... .......... .......... .......... 83%  954G 2s
212400K .......... .......... .......... .......... .......... 83%  331M 2s
212450K .......... .......... .......... .......... .......... 83% 10,7M 2s
212500K .......... .......... .......... .......... .......... 83%  200M 2s
212550K .......... .......... .......... .......... .......... 83%  954G 2s
212600K .......... .......... .......... .......... .......... 83%  255M 2s
212650K .......... .......... .......... .......... .......... 83%  284M 2s
212700K .......... .......... .......... .......... .......... 83%  191M 2s
212750K .......... .......... .......... .......... .......... 83%  954G 2s
212800K .......... .......... .......... .......... .......... 83%  265M 2s
212850K .......... .......... .......... .......... .......... 83%  205M 2s
212900K .......... .......... .......... .......... .......... 83%  252M 2s
212950K .......... .......... .......... .......... .......... 83% 82,5M 2s
213000K .......... .......... .......... .......... .......... 83%  954G 2s
213050K .......... .......... .......... .......... .......... 83%  121M 2s
213100K .......... .......... .......... .......... .......... 83%  135M 2s
213150K .......... .......... .......... .......... .......... 83%  114M 2s
213200K .......... .......... .......... .......... .......... 83%  115M 2s
213250K .......... .......... .......... .......... .......... 83%  954G 2s
213300K .......... .......... .......... .......... .......... 83%  114M 2s
213350K .......... .......... .......... .......... .......... 83%  119M 2s
213400K .......... .......... .......... .......... .......... 83%  193M 2s
213450K .......... .......... .......... .......... .......... 83%  954G 2s
213500K .......... .......... .......... .......... .......... 83% 43,3M 2s
213550K .......... .......... .......... .......... .......... 83% 31,4M 2s
213600K .......... .......... .......... .......... .......... 83% 34,1M 2s
213650K .......... .......... .......... .......... .......... 83% 30,8M 2s
213700K .......... .......... .......... .......... .......... 83% 34,9M 2s
213750K .......... .......... .......... .......... .......... 83% 10,4M 2s
213800K .......... .......... .......... .......... .......... 83%  134M 2s
213850K .......... .......... .......... .......... .......... 83% 3,07M 2s
213900K .......... .......... .......... .......... .......... 83%  954G 2s
213950K .......... .......... .......... .......... .......... 83% 57,4M 2s
214000K .......... .......... .......... .......... .......... 83% 16,6M 2s
214050K .......... .......... .......... .......... .......... 83% 14,1M 2s
214100K .......... .......... .......... .......... .......... 83% 22,0M 2s
214150K .......... .......... .......... .......... .......... 83% 18,8M 2s
214200K .......... .......... .......... .......... .......... 83% 39,6M 2s
214250K .......... .......... .......... .......... .......... 83% 34,0M 2s
214300K .......... .......... .......... .......... .......... 84% 24,5M 2s
214350K .......... .......... .......... .......... .......... 84% 54,1M 2s
214400K .......... .......... .......... .......... .......... 84% 11,7M 2s
214450K .......... .......... .......... .......... .......... 84% 13,5M 2s
214500K .......... .......... .......... .......... .......... 84% 19,1M 2s
214550K .......... .......... .......... .......... .......... 84% 51,7M 2s
214600K .......... .......... .......... .......... .......... 84% 57,8M 2s
214650K .......... .......... .......... .......... .......... 84% 23,7M 2s
214700K .......... .......... .......... .......... .......... 84% 32,4M 2s
214750K .......... .......... .......... .......... .......... 84% 41,5M 2s
214800K .......... .......... .......... .......... .......... 84% 18,5M 2s
214850K .......... .......... .......... .......... .......... 84% 61,7M 2s
214900K .......... .......... .......... .......... .......... 84% 29,7M 2s
214950K .......... .......... .......... .......... .......... 84% 30,4M 2s
215000K .......... .......... .......... .......... .......... 84% 28,4M 2s
215050K .......... .......... .......... .......... .......... 84% 50,7M 2s
215100K .......... .......... .......... .......... .......... 84% 26,3M 2s
215150K .......... .......... .......... .......... .......... 84% 16,4M 2s
215200K .......... .......... .......... .......... .......... 84% 39,3M 2s
215250K .......... .......... .......... .......... .......... 84% 13,5M 2s
215300K .......... .......... .......... .......... .......... 84% 61,1M 2s
215350K .......... .......... .......... .......... .......... 84% 11,0M 2s
215400K .......... .......... .......... .......... .......... 84% 44,2M 2s
215450K .......... .......... .......... .......... .......... 84%  166M 2s
215500K .......... .......... .......... .......... .......... 84% 21,3M 2s
215550K .......... .......... .......... .......... .......... 84%  101M 2s
215600K .......... .......... .......... .......... .......... 84% 84,7M 2s
215650K .......... .......... .......... .......... .......... 84% 18,1M 2s
215700K .......... .......... .......... .......... .......... 84% 75,3M 2s
215750K .......... .......... .......... .......... .......... 84% 6,54M 2s
215800K .......... .......... .......... .......... .......... 84%  954G 2s
215850K .......... .......... .......... .......... .......... 84% 20,9M 2s
215900K .......... .......... .......... .......... .......... 84% 40,5M 2s
215950K .......... .......... .......... .......... .......... 84% 28,9M 2s
216000K .......... .......... .......... .......... .......... 84%  954G 2s
216050K .......... .......... .......... .......... .......... 84% 41,6M 2s
216100K .......... .......... .......... .......... .......... 84%  110M 2s
216150K .......... .......... .......... .......... .......... 84% 60,2M 2s
216200K .......... .......... .......... .......... .......... 84% 20,5M 2s
216250K .......... .......... .......... .......... .......... 84% 42,2M 2s
216300K .......... .......... .......... .......... .......... 84% 15,2M 2s
216350K .......... .......... .......... .......... .......... 84% 33,9M 2s
216400K .......... .......... .......... .......... .......... 84% 31,0M 2s
216450K .......... .......... .......... .......... .......... 84% 35,3M 2s
216500K .......... .......... .......... .......... .......... 84% 14,0M 2s
216550K .......... .......... .......... .......... .......... 84% 44,6M 2s
216600K .......... .......... .......... .......... .......... 84% 33,9M 2s
216650K .......... .......... .......... .......... .......... 84% 43,8M 2s
216700K .......... .......... .......... .......... .......... 84% 33,6M 2s
216750K .......... .......... .......... .......... .......... 84% 24,9M 2s
216800K .......... .......... .......... .......... .......... 84% 48,3M 2s
216850K .......... .......... .......... .......... .......... 85% 31,1M 2s
216900K .......... .......... .......... .......... .......... 85% 25,8M 2s
216950K .......... .......... .......... .......... .......... 85% 14,8M 2s
217000K .......... .......... .......... .......... .......... 85% 18,1M 2s
217050K .......... .......... .......... .......... .......... 85% 45,0M 2s
217100K .......... .......... .......... .......... .......... 85% 38,4M 2s
217150K .......... .......... .......... .......... .......... 85% 1,09M 2s
217200K .......... .......... .......... .......... .......... 85%  954G 2s
217250K .......... .......... .......... .......... .......... 85% 19,1M 2s
217300K .......... .......... .......... .......... .......... 85% 38,5M 2s
217350K .......... .......... .......... .......... .......... 85%  954G 2s
217400K .......... .......... .......... .......... .......... 85% 17,5M 2s
217450K .......... .......... .......... .......... .......... 85% 56,2M 2s
217500K .......... .......... .......... .......... .......... 85%  239M 2s
217550K .......... .......... .......... .......... .......... 85% 28,6M 2s
217600K .......... .......... .......... .......... .......... 85%  230M 2s
217650K .......... .......... .......... .......... .......... 85% 21,4M 2s
217700K .......... .......... .......... .......... .......... 85%  954G 2s
217750K .......... .......... .......... .......... .......... 85% 28,7M 2s
217800K .......... .......... .......... .......... .......... 85% 41,8M 2s
217850K .......... .......... .......... .......... .......... 85% 8,21M 2s
217900K .......... .......... .......... .......... .......... 85% 65,1M 2s
217950K .......... .......... .......... .......... .......... 85% 38,1M 2s
218000K .......... .......... .......... .......... .......... 85% 30,6M 2s
218050K .......... .......... .......... .......... .......... 85%  954G 2s
218100K .......... .......... .......... .......... .......... 85%  292M 2s
218150K .......... .......... .......... .......... .......... 85%  223M 2s
218200K .......... .......... .......... .......... .......... 85%  361M 2s
218250K .......... .......... .......... .......... .......... 85%  415M 2s
218300K .......... .......... .......... .......... .......... 85%  954G 2s
218350K .......... .......... .......... .......... .......... 85%  346M 2s
218400K .......... .......... .......... .......... .......... 85%  129M 2s
218450K .......... .......... .......... .......... .......... 85%  339M 2s
218500K .......... .......... .......... .......... .......... 85%  954G 2s
218550K .......... .......... .......... .......... .......... 85%  326M 2s
218600K .......... .......... .......... .......... .......... 85%  324M 2s
218650K .......... .......... .......... .......... .......... 85%  101M 2s
218700K .......... .......... .......... .......... .......... 85%  206M 2s
218750K .......... .......... .......... .......... .......... 85%  954G 2s
218800K .......... .......... .......... .......... .......... 85%  164M 2s
218850K .......... .......... .......... .......... .......... 85%  226M 2s
218900K .......... .......... .......... .......... .......... 85% 9,92M 2s
218950K .......... .......... .......... .......... .......... 85% 7,63M 2s
219000K .......... .......... .......... .......... .......... 85% 32,5M 2s
219050K .......... .......... .......... .......... .......... 85% 51,8M 2s
219100K .......... .......... .......... .......... .......... 85%  174M 2s
219150K .......... .......... .......... .......... .......... 85% 32,5M 2s
219200K .......... .......... .......... .......... .......... 85% 35,3M 2s
219250K .......... .......... .......... .......... .......... 85% 17,1M 2s
219300K .......... .......... .......... .......... .......... 85% 28,6M 2s
219350K .......... .......... .......... .......... .......... 85% 28,5M 2s
219400K .......... .......... .......... .......... .......... 86% 38,3M 2s
219450K .......... .......... .......... .......... .......... 86% 28,7M 2s
219500K .......... .......... .......... .......... .......... 86% 24,8M 2s
219550K .......... .......... .......... .......... .......... 86% 27,3M 2s
219600K .......... .......... .......... .......... .......... 86% 47,9M 2s
219650K .......... .......... .......... .......... .......... 86% 22,0M 2s
219700K .......... .......... .......... .......... .......... 86% 39,0M 2s
219750K .......... .......... .......... .......... .......... 86% 45,1M 2s
219800K .......... .......... .......... .......... .......... 86% 36,2M 2s
219850K .......... .......... .......... .......... .......... 86% 33,1M 2s
219900K .......... .......... .......... .......... .......... 86% 31,9M 2s
219950K .......... .......... .......... .......... .......... 86% 41,3M 2s
220000K .......... .......... .......... .......... .......... 86% 26,2M 2s
220050K .......... .......... .......... .......... .......... 86% 22,4M 2s
220100K .......... .......... .......... .......... .......... 86% 41,6M 2s
220150K .......... .......... .......... .......... .......... 86% 32,0M 2s
220200K .......... .......... .......... .......... .......... 86% 37,3M 2s
220250K .......... .......... .......... .......... .......... 86% 25,5M 2s
220300K .......... .......... .......... .......... .......... 86% 34,5M 2s
220350K .......... .......... .......... .......... .......... 86% 57,0M 2s
220400K .......... .......... .......... .......... .......... 86% 29,5M 2s
220450K .......... .......... .......... .......... .......... 86% 18,4M 2s
220500K .......... .......... .......... .......... .......... 86% 61,2M 2s
220550K .......... .......... .......... .......... .......... 86% 30,1M 2s
220600K .......... .......... .......... .......... .......... 86% 10,3M 2s
220650K .......... .......... .......... .......... .......... 86% 49,0M 2s
220700K .......... .......... .......... .......... .......... 86% 29,8M 2s
220750K .......... .......... .......... .......... .......... 86% 44,4M 2s
220800K .......... .......... .......... .......... .......... 86% 33,2M 2s
220850K .......... .......... .......... .......... .......... 86% 18,5M 2s
220900K .......... .......... .......... .......... .......... 86% 19,4M 2s
220950K .......... .......... .......... .......... .......... 86%  160M 2s
221000K .......... .......... .......... .......... .......... 86% 40,3M 2s
221050K .......... .......... .......... .......... .......... 86% 30,6M 2s
221100K .......... .......... .......... .......... .......... 86% 30,0M 2s
221150K .......... .......... .......... .......... .......... 86% 29,2M 2s
221200K .......... .......... .......... .......... .......... 86% 34,5M 2s
221250K .......... .......... .......... .......... .......... 86% 21,5M 2s
221300K .......... .......... .......... .......... .......... 86% 34,4M 2s
221350K .......... .......... .......... .......... .......... 86% 27,9M 2s
221400K .......... .......... .......... .......... .......... 86% 21,8M 2s
221450K .......... .......... .......... .......... .......... 86%  106M 2s
221500K .......... .......... .......... .......... .......... 86% 48,3M 2s
221550K .......... .......... .......... .......... .......... 86% 36,7M 2s
221600K .......... .......... .......... .......... .......... 86% 41,8M 2s
221650K .......... .......... .......... .......... .......... 86% 13,4M 2s
221700K .......... .......... .......... .......... .......... 86% 96,6M 1s
221750K .......... .......... .......... .......... .......... 86% 9,91M 1s
221800K .......... .......... .......... .......... .......... 86% 26,7M 1s
221850K .......... .......... .......... .......... .......... 86% 28,2M 1s
221900K .......... .......... .......... .......... .......... 86% 30,0M 1s
221950K .......... .......... .......... .......... .......... 87% 32,7M 1s
222000K .......... .......... .......... .......... .......... 87% 45,0M 1s
222050K .......... .......... .......... .......... .......... 87% 29,0M 1s
222100K .......... .......... .......... .......... .......... 87% 31,7M 1s
222150K .......... .......... .......... .......... .......... 87% 35,4M 1s
222200K .......... .......... .......... .......... .......... 87% 11,0M 1s
222250K .......... .......... .......... .......... .......... 87% 36,0M 1s
222300K .......... .......... .......... .......... .......... 87% 33,5M 1s
222350K .......... .......... .......... .......... .......... 87% 34,0M 1s
222400K .......... .......... .......... .......... .......... 87% 40,5M 1s
222450K .......... .......... .......... .......... .......... 87% 35,0M 1s
222500K .......... .......... .......... .......... .......... 87% 45,9M 1s
222550K .......... .......... .......... .......... .......... 87% 30,9M 1s
222600K .......... .......... .......... .......... .......... 87% 30,4M 1s
222650K .......... .......... .......... .......... .......... 87% 14,1M 1s
222700K .......... .......... .......... .......... .......... 87% 40,3M 1s
222750K .......... .......... .......... .......... .......... 87% 38,0M 1s
222800K .......... .......... .......... .......... .......... 87% 27,9M 1s
222850K .......... .......... .......... .......... .......... 87% 35,7M 1s
222900K .......... .......... .......... .......... .......... 87% 28,0M 1s
222950K .......... .......... .......... .......... .......... 87% 34,2M 1s
223000K .......... .......... .......... .......... .......... 87% 45,4M 1s
223050K .......... .......... .......... .......... .......... 87%  978K 1s
223100K .......... .......... .......... .......... .......... 87%  212M 1s
223150K .......... .......... .......... .......... .......... 87%  954G 1s
223200K .......... .......... .......... .......... .......... 87% 81,7M 1s
223250K .......... .......... .......... .......... .......... 87% 1024K 1s
223300K .......... .......... .......... .......... .......... 87%  259M 1s
223350K .......... .......... .......... .......... .......... 87%  385M 1s
223400K .......... .......... .......... .......... .......... 87%  410M 1s
223450K .......... .......... .......... .......... .......... 87% 8,94M 1s
223500K .......... .......... .......... .......... .......... 87%  954G 1s
223550K .......... .......... .......... .......... .......... 87%  213M 1s
223600K .......... .......... .......... .......... .......... 87%  367M 1s
223650K .......... .......... .......... .......... .......... 87%  410M 1s
223700K .......... .......... .......... .......... .......... 87%  414M 1s
223750K .......... .......... .......... .......... .......... 87%  954G 1s
223800K .......... .......... .......... .......... .......... 87%  158M 1s
223850K .......... .......... .......... .......... .......... 87%  185M 1s
223900K .......... .......... .......... .......... .......... 87%  185M 1s
223950K .......... .......... .......... .......... .......... 87%  411M 1s
224000K .......... .......... .......... .......... .......... 87%  954G 1s
224050K .......... .......... .......... .......... .......... 87%  391M 1s
224100K .......... .......... .......... .......... .......... 87%  431M 1s
224150K .......... .......... .......... .......... .......... 87%  419M 1s
224200K .......... .......... .......... .......... .......... 87%  954G 1s
224250K .......... .......... .......... .......... .......... 87%  410M 1s
224300K .......... .......... .......... .......... .......... 87%  285M 1s
224350K .......... .......... .......... .......... .......... 87%  388M 1s
224400K .......... .......... .......... .......... .......... 87%  417M 1s
224450K .......... .......... .......... .......... .......... 87%  954G 1s
224500K .......... .......... .......... .......... .......... 88%  391M 1s
224550K .......... .......... .......... .......... .......... 88%  110M 1s
224600K .......... .......... .......... .......... .......... 88%  187M 1s
224650K .......... .......... .......... .......... .......... 88%  954G 1s
224700K .......... .......... .......... .......... .......... 88% 28,7M 1s
224750K .......... .......... .......... .......... .......... 88%  141M 1s
224800K .......... .......... .......... .......... .......... 88%  210M 1s
224850K .......... .......... .......... .......... .......... 88%  236M 1s
224900K .......... .......... .......... .......... .......... 88%  954G 1s
224950K .......... .......... .......... .......... .......... 88%  117M 1s
225000K .......... .......... .......... .......... .......... 88% 69,3M 1s
225050K .......... .......... .......... .......... .......... 88%  210M 1s
225100K .......... .......... .......... .......... .......... 88%  954G 1s
225150K .......... .......... .......... .......... .......... 88%  278M 1s
225200K .......... .......... .......... .......... .......... 88%  327M 1s
225250K .......... .......... .......... .......... .......... 88%  326M 1s
225300K .......... .......... .......... .......... .......... 88%  239M 1s
225350K .......... .......... .......... .......... .......... 88%  954G 1s
225400K .......... .......... .......... .......... .......... 88%  299M 1s
225450K .......... .......... .......... .......... .......... 88%  307M 1s
225500K .......... .......... .......... .......... .......... 88%  331M 1s
225550K .......... .......... .......... .......... .......... 88%  201M 1s
225600K .......... .......... .......... .......... .......... 88%  954G 1s
225650K .......... .......... .......... .......... .......... 88%  203M 1s
225700K .......... .......... .......... .......... .......... 88%  396M 1s
225750K .......... .......... .......... .......... .......... 88%  334M 1s
225800K .......... .......... .......... .......... .......... 88% 2,46M 1s
225850K .......... .......... .......... .......... .......... 88%  107M 1s
225900K .......... .......... .......... .......... .......... 88%  111M 1s
225950K .......... .......... .......... .......... .......... 88%  128M 1s
226000K .......... .......... .......... .......... .......... 88%  101M 1s
226050K .......... .......... .......... .......... .......... 88%  115M 1s
226100K .......... .......... .......... .......... .......... 88% 90,5M 1s
226150K .......... .......... .......... .......... .......... 88% 87,9M 1s
226200K .......... .......... .......... .......... .......... 88% 55,4M 1s
226250K .......... .......... .......... .......... .......... 88% 96,5M 1s
226300K .......... .......... .......... .......... .......... 88% 99,9M 1s
226350K .......... .......... .......... .......... .......... 88%  121M 1s
226400K .......... .......... .......... .......... .......... 88% 92,8M 1s
226450K .......... .......... .......... .......... .......... 88%  122M 1s
226500K .......... .......... .......... .......... .......... 88%  120M 1s
226550K .......... .......... .......... .......... .......... 88% 50,1M 1s
226600K .......... .......... .......... .......... .......... 88%  144M 1s
226650K .......... .......... .......... .......... .......... 88% 36,6M 1s
226700K .......... .......... .......... .......... .......... 88% 13,3M 1s
226750K .......... .......... .......... .......... .......... 88% 36,6M 1s
226800K .......... .......... .......... .......... .......... 88% 18,6M 1s
226850K .......... .......... .......... .......... .......... 88% 9,81M 1s
226900K .......... .......... .......... .......... .......... 88% 13,7M 1s
226950K .......... .......... .......... .......... .......... 88% 18,8M 1s
227000K .......... .......... .......... .......... .......... 88% 26,7M 1s
227050K .......... .......... .......... .......... .......... 89% 47,6M 1s
227100K .......... .......... .......... .......... .......... 89% 29,5M 1s
227150K .......... .......... .......... .......... .......... 89% 21,3M 1s
227200K .......... .......... .......... .......... .......... 89% 38,5M 1s
227250K .......... .......... .......... .......... .......... 89% 26,3M 1s
227300K .......... .......... .......... .......... .......... 89% 38,6M 1s
227350K .......... .......... .......... .......... .......... 89% 36,6M 1s
227400K .......... .......... .......... .......... .......... 89% 33,4M 1s
227450K .......... .......... .......... .......... .......... 89% 25,1M 1s
227500K .......... .......... .......... .......... .......... 89% 32,5M 1s
227550K .......... .......... .......... .......... .......... 89% 35,3M 1s
227600K .......... .......... .......... .......... .......... 89% 14,2M 1s
227650K .......... .......... .......... .......... .......... 89% 30,4M 1s
227700K .......... .......... .......... .......... .......... 89% 15,5M 1s
227750K .......... .......... .......... .......... .......... 89% 39,8M 1s
227800K .......... .......... .......... .......... .......... 89% 4,92M 1s
227850K .......... .......... .......... .......... .......... 89%  129M 1s
227900K .......... .......... .......... .......... .......... 89%  177M 1s
227950K .......... .......... .......... .......... .......... 89%  193M 1s
228000K .......... .......... .......... .......... .......... 89% 74,8M 1s
228050K .......... .......... .......... .......... .......... 89%  149M 1s
228100K .......... .......... .......... .......... .......... 89% 77,7M 1s
228150K .......... .......... .......... .......... .......... 89%  111M 1s
228200K .......... .......... .......... .......... .......... 89% 47,5M 1s
228250K .......... .......... .......... .......... .......... 89% 37,0M 1s
228300K .......... .......... .......... .......... .......... 89% 23,9M 1s
228350K .......... .......... .......... .......... .......... 89% 29,9M 1s
228400K .......... .......... .......... .......... .......... 89% 14,7M 1s
228450K .......... .......... .......... .......... .......... 89% 31,4M 1s
228500K .......... .......... .......... .......... .......... 89% 30,0M 1s
228550K .......... .......... .......... .......... .......... 89% 33,8M 1s
228600K .......... .......... .......... .......... .......... 89% 32,1M 1s
228650K .......... .......... .......... .......... .......... 89% 38,1M 1s
228700K .......... .......... .......... .......... .......... 89% 24,5M 1s
228750K .......... .......... .......... .......... .......... 89% 38,9M 1s
228800K .......... .......... .......... .......... .......... 89% 14,2M 1s
228850K .......... .......... .......... .......... .......... 89% 24,2M 1s
228900K .......... .......... .......... .......... .......... 89% 26,4M 1s
228950K .......... .......... .......... .......... .......... 89%  954G 1s
229000K .......... .......... .......... .......... .......... 89% 32,5M 1s
229050K .......... .......... .......... .......... .......... 89% 26,5M 1s
229100K .......... .......... .......... .......... .......... 89% 15,7M 1s
229150K .......... .......... .......... .......... .......... 89% 30,8M 1s
229200K .......... .......... .......... .......... .......... 89% 15,9M 1s
229250K .......... .......... .......... .......... .......... 89% 8,94M 1s
229300K .......... .......... .......... .......... .......... 89%  158M 1s
229350K .......... .......... .......... .......... .......... 89%  199M 1s
229400K .......... .......... .......... .......... .......... 89%  180M 1s
229450K .......... .......... .......... .......... .......... 89% 83,6M 1s
229500K .......... .......... .......... .......... .......... 89% 44,9M 1s
229550K .......... .......... .......... .......... .......... 89% 44,3M 1s
229600K .......... .......... .......... .......... .......... 89% 25,0M 1s
229650K .......... .......... .......... .......... .......... 90% 11,8M 1s
229700K .......... .......... .......... .......... .......... 90% 26,1M 1s
229750K .......... .......... .......... .......... .......... 90% 6,29M 1s
229800K .......... .......... .......... .......... .......... 90%  148M 1s
229850K .......... .......... .......... .......... .......... 90%  229M 1s
229900K .......... .......... .......... .......... .......... 90%  196M 1s
229950K .......... .......... .......... .......... .......... 90% 10,5M 1s
230000K .......... .......... .......... .......... .......... 90% 1,28M 1s
230050K .......... .......... .......... .......... .......... 90% 13,6M 1s
230100K .......... .......... .......... .......... .......... 90%  954G 1s
230150K .......... .......... .......... .......... .......... 90% 27,8M 1s
230200K .......... .......... .......... .......... .......... 90% 42,0M 1s
230250K .......... .......... .......... .......... .......... 90%  100M 1s
230300K .......... .......... .......... .......... .......... 90%  119M 1s
230350K .......... .......... .......... .......... .......... 90%  142M 1s
230400K .......... .......... .......... .......... .......... 90%  215M 1s
230450K .......... .......... .......... .......... .......... 90%  168M 1s
230500K .......... .......... .......... .......... .......... 90%  175M 1s
230550K .......... .......... .......... .......... .......... 90%  954G 1s
230600K .......... .......... .......... .......... .......... 90%  379M 1s
230650K .......... .......... .......... .......... .......... 90% 4,90M 1s
230700K .......... .......... .......... .......... .......... 90%  282M 1s
230750K .......... .......... .......... .......... .......... 90%  316M 1s
230800K .......... .......... .......... .......... .......... 90%  954G 1s
230850K .......... .......... .......... .......... .......... 90%  364M 1s
230900K .......... .......... .......... .......... .......... 90% 4,20M 1s
230950K .......... .......... .......... .......... .......... 90%  448M 1s
231000K .......... .......... .......... .......... .......... 90%  412M 1s
231050K .......... .......... .......... .......... .......... 90% 9,93M 1s
231100K .......... .......... .......... .......... .......... 90% 23,6M 1s
231150K .......... .......... .......... .......... .......... 90% 37,9M 1s
231200K .......... .......... .......... .......... .......... 90% 19,9M 1s
231250K .......... .......... .......... .......... .......... 90% 32,0M 1s
231300K .......... .......... .......... .......... .......... 90% 59,2M 1s
231350K .......... .......... .......... .......... .......... 90%  311M 1s
231400K .......... .......... .......... .......... .......... 90%  269M 1s
231450K .......... .......... .......... .......... .......... 90%  412M 1s
231500K .......... .......... .......... .......... .......... 90%  954G 1s
231550K .......... .......... .......... .......... .......... 90%  184M 1s
231600K .......... .......... .......... .......... .......... 90%  387M 1s
231650K .......... .......... .......... .......... .......... 90%  392M 1s
231700K .......... .......... .......... .......... .......... 90%  954G 1s
231750K .......... .......... .......... .......... .......... 90%  210M 1s
231800K .......... .......... .......... .......... .......... 90%  420M 1s
231850K .......... .......... .......... .......... .......... 90%  416M 1s
231900K .......... .......... .......... .......... .......... 90%  214M 1s
231950K .......... .......... .......... .......... .......... 90%  954G 1s
232000K .......... .......... .......... .......... .......... 90%  400M 1s
232050K .......... .......... .......... .......... .......... 90%  241M 1s
232100K .......... .......... .......... .......... .......... 90%  164M 1s
232150K .......... .......... .......... .......... .......... 90%  954G 1s
232200K .......... .......... .......... .......... .......... 91% 22,8M 1s
232250K .......... .......... .......... .......... .......... 91% 50,6M 1s
232300K .......... .......... .......... .......... .......... 91% 7,43M 1s
232350K .......... .......... .......... .......... .......... 91% 39,7M 1s
232400K .......... .......... .......... .......... .......... 91% 51,7M 1s
232450K .......... .......... .......... .......... .......... 91% 7,22M 1s
232500K .......... .......... .......... .......... .......... 91%  103M 1s
232550K .......... .......... .......... .......... .......... 91%  110M 1s
232600K .......... .......... .......... .......... .......... 91% 37,9M 1s
232650K .......... .......... .......... .......... .......... 91% 3,20M 1s
232700K .......... .......... .......... .......... .......... 91% 1,12M 1s
232750K .......... .......... .......... .......... .......... 91%  378M 1s
232800K .......... .......... .......... .......... .......... 91%  183M 1s
232850K .......... .......... .......... .......... .......... 91% 13,4M 1s
232900K .......... .......... .......... .......... .......... 91%  168M 1s
232950K .......... .......... .......... .......... .......... 91%  296M 1s
233000K .......... .......... .......... .......... .......... 91%  396M 1s
233050K .......... .......... .......... .......... .......... 91%  196M 1s
233100K .......... .......... .......... .......... .......... 91% 6,33M 1s
233150K .......... .......... .......... .......... .......... 91%  302M 1s
233200K .......... .......... .......... .......... .......... 91% 18,9M 1s
233250K .......... .......... .......... .......... .......... 91%  222M 1s
233300K .......... .......... .......... .......... .......... 91% 16,2M 1s
233350K .......... .......... .......... .......... .......... 91%  182M 1s
233400K .......... .......... .......... .......... .......... 91%  954G 1s
233450K .......... .......... .......... .......... .......... 91%  237M 1s
233500K .......... .......... .......... .......... .......... 91% 11,0M 1s
233550K .......... .......... .......... .......... .......... 91% 21,0M 1s
233600K .......... .......... .......... .......... .......... 91%  380M 1s
233650K .......... .......... .......... .......... .......... 91%  954G 1s
233700K .......... .......... .......... .......... .......... 91% 5,16M 1s
233750K .......... .......... .......... .......... .......... 91% 38,8M 1s
233800K .......... .......... .......... .......... .......... 91% 12,9M 1s
233850K .......... .......... .......... .......... .......... 91% 40,6M 1s
233900K .......... .......... .......... .......... .......... 91% 94,0M 1s
233950K .......... .......... .......... .......... .......... 91% 18,8M 1s
234000K .......... .......... .......... .......... .......... 91%  954G 1s
234050K .......... .......... .......... .......... .......... 91% 17,0M 1s
234100K .......... .......... .......... .......... .......... 91%  226M 1s
234150K .......... .......... .......... .......... .......... 91%  166M 1s
234200K .......... .......... .......... .......... .......... 91% 28,8M 1s
234250K .......... .......... .......... .......... .......... 91%  290M 1s
234300K .......... .......... .......... .......... .......... 91%  954G 1s
234350K .......... .......... .......... .......... .......... 91%  383M 1s
234400K .......... .......... .......... .......... .......... 91%  415M 1s
234450K .......... .......... .......... .......... .......... 91%  413M 1s
234500K .......... .......... .......... .......... .......... 91%  254M 1s
234550K .......... .......... .......... .......... .......... 91%  954G 1s
234600K .......... .......... .......... .......... .......... 91%  374M 1s
234650K .......... .......... .......... .......... .......... 91%  418M 1s
234700K .......... .......... .......... .......... .......... 91%  171M 1s
234750K .......... .......... .......... .......... .......... 92%  954G 1s
234800K .......... .......... .......... .......... .......... 92%  133M 1s
234850K .......... .......... .......... .......... .......... 92%  275M 1s
234900K .......... .......... .......... .......... .......... 92%  396M 1s
234950K .......... .......... .......... .......... .......... 92%  412M 1s
235000K .......... .......... .......... .......... .......... 92%  954G 1s
235050K .......... .......... .......... .......... .......... 92%  363M 1s
235100K .......... .......... .......... .......... .......... 92%  382M 1s
235150K .......... .......... .......... .......... .......... 92%  355M 1s
235200K .......... .......... .......... .......... .......... 92%  202M 1s
235250K .......... .......... .......... .......... .......... 92%  954G 1s
235300K .......... .......... .......... .......... .......... 92%  145M 1s
235350K .......... .......... .......... .......... .......... 92%  343M 1s
235400K .......... .......... .......... .......... .......... 92%  419M 1s
235450K .......... .......... .......... .......... .......... 92%  954G 1s
235500K .......... .......... .......... .......... .......... 92% 65,0M 1s
235550K .......... .......... .......... .......... .......... 92% 23,6M 1s
235600K .......... .......... .......... .......... .......... 92% 37,4M 1s
235650K .......... .......... .......... .......... .......... 92% 37,0M 1s
235700K .......... .......... .......... .......... .......... 92% 16,1M 1s
235750K .......... .......... .......... .......... .......... 92% 13,8M 1s
235800K .......... .......... .......... .......... .......... 92% 34,4M 1s
235850K .......... .......... .......... .......... .......... 92% 19,9M 1s
235900K .......... .......... .......... .......... .......... 92% 37,4M 1s
235950K .......... .......... .......... .......... .......... 92% 37,5M 1s
236000K .......... .......... .......... .......... .......... 92% 13,6M 1s
236050K .......... .......... .......... .......... .......... 92% 1,09M 1s
236100K .......... .......... .......... .......... .......... 92%  585K 1s
236150K .......... .......... .......... .......... .......... 92% 28,4M 1s
236200K .......... .......... .......... .......... .......... 92% 28,2M 1s
236250K .......... .......... .......... .......... .......... 92% 18,9M 1s
236300K .......... .......... .......... .......... .......... 92% 19,4M 1s
236350K .......... .......... .......... .......... .......... 92%  954G 1s
236400K .......... .......... .......... .......... .......... 92% 22,0M 1s
236450K .......... .......... .......... .......... .......... 92% 36,3M 1s
236500K .......... .......... .......... .......... .......... 92% 31,1M 1s
236550K .......... .......... .......... .......... .......... 92% 28,1M 1s
236600K .......... .......... .......... .......... .......... 92%  954G 1s
236650K .......... .......... .......... .......... .......... 92% 62,2M 1s
236700K .......... .......... .......... .......... .......... 92%  256M 1s
236750K .......... .......... .......... .......... .......... 92%  133M 1s
236800K .......... .......... .......... .......... .......... 92%  954G 1s
236850K .......... .......... .......... .......... .......... 92%  276M 1s
236900K .......... .......... .......... .......... .......... 92%  287M 1s
236950K .......... .......... .......... .......... .......... 92%  296M 1s
237000K .......... .......... .......... .......... .......... 92%  156M 1s
237050K .......... .......... .......... .......... .......... 92%  954G 1s
237100K .......... .......... .......... .......... .......... 92%  103M 1s
237150K .......... .......... .......... .......... .......... 92% 48,3M 1s
237200K .......... .......... .......... .......... .......... 92% 42,2M 1s
237250K .......... .......... .......... .......... .......... 92%  954G 1s
237300K .......... .......... .......... .......... .......... 93% 59,2M 1s
237350K .......... .......... .......... .......... .......... 93% 40,0M 1s
237400K .......... .......... .......... .......... .......... 93% 55,8M 1s
237450K .......... .......... .......... .......... .......... 93% 41,5M 1s
237500K .......... .......... .......... .......... .......... 93%  954G 1s
237550K .......... .......... .......... .......... .......... 93% 33,3M 1s
237600K .......... .......... .......... .......... .......... 93% 28,9M 1s
237650K .......... .......... .......... .......... .......... 93% 20,2M 1s
237700K .......... .......... .......... .......... .......... 93%  954G 1s
237750K .......... .......... .......... .......... .......... 93% 23,7M 1s
237800K .......... .......... .......... .......... .......... 93% 53,7M 1s
237850K .......... .......... .......... .......... .......... 93% 32,4M 1s
237900K .......... .......... .......... .......... .......... 93% 44,5M 1s
237950K .......... .......... .......... .......... .......... 93%  954G 1s
238000K .......... .......... .......... .......... .......... 93% 61,6M 1s
238050K .......... .......... .......... .......... .......... 93% 94,2M 1s
238100K .......... .......... .......... .......... .......... 93%  247M 1s
238150K .......... .......... .......... .......... .......... 93%  131M 1s
238200K .......... .......... .......... .......... .......... 93%  954G 1s
238250K .......... .......... .......... .......... .......... 93% 81,8M 1s
238300K .......... .......... .......... .......... .......... 93%  251M 1s
238350K .......... .......... .......... .......... .......... 93% 62,3M 1s
238400K .......... .......... .......... .......... .......... 93%  954G 1s
238450K .......... .......... .......... .......... .......... 93%  119M 1s
238500K .......... .......... .......... .......... .......... 93% 84,4M 1s
238550K .......... .......... .......... .......... .......... 93% 33,9M 1s
238600K .......... .......... .......... .......... .......... 93% 1,22M 1s
238650K .......... .......... .......... .......... .......... 93%  106M 1s
238700K .......... .......... .......... .......... .......... 93%  954G 1s
238750K .......... .......... .......... .......... .......... 93%  273M 1s
238800K .......... .......... .......... .......... .......... 93%  378M 1s
238850K .......... .......... .......... .......... .......... 93%  161M 1s
238900K .......... .......... .......... .......... .......... 93%  954G 1s
238950K .......... .......... .......... .......... .......... 93%  290M 1s
239000K .......... .......... .......... .......... .......... 93%  397M 1s
239050K .......... .......... .......... .......... .......... 93%  153M 1s
239100K .......... .......... .......... .......... .......... 93%  276M 1s
239150K .......... .......... .......... .......... .......... 93%  954G 1s
239200K .......... .......... .......... .......... .......... 93%  320M 1s
239250K .......... .......... .......... .......... .......... 93%  315M 1s
239300K .......... .......... .......... .......... .......... 93%  253M 1s
239350K .......... .......... .......... .......... .......... 93%  265M 1s
239400K .......... .......... .......... .......... .......... 93%  954G 1s
239450K .......... .......... .......... .......... .......... 93%  222M 1s
239500K .......... .......... .......... .......... .......... 93%  259M 1s
239550K .......... .......... .......... .......... .......... 93%  337M 1s
239600K .......... .......... .......... .......... .......... 93%  954G 1s
239650K .......... .......... .......... .......... .......... 93%  176M 1s
239700K .......... .......... .......... .......... .......... 93%  112M 1s
239750K .......... .......... .......... .......... .......... 93%  322M 1s
239800K .......... .......... .......... .......... .......... 93%  386M 1s
239850K .......... .......... .......... .......... .......... 94%  954G 1s
239900K .......... .......... .......... .......... .......... 94%  125M 1s
239950K .......... .......... .......... .......... .......... 94%  198M 1s
240000K .......... .......... .......... .......... .......... 94%  281M 1s
240050K .......... .......... .......... .......... .......... 94%  954G 1s
240100K .......... .......... .......... .......... .......... 94%  303M 1s
240150K .......... .......... .......... .......... .......... 94%  315M 1s
240200K .......... .......... .......... .......... .......... 94%  359M 1s
240250K .......... .......... .......... .......... .......... 94%  105M 1s
240300K .......... .......... .......... .......... .......... 94%  954G 1s
240350K .......... .......... .......... .......... .......... 94% 36,1M 1s
240400K .......... .......... .......... .......... .......... 94% 55,8M 1s
240450K .......... .......... .......... .......... .......... 94%  139M 1s
240500K .......... .......... .......... .......... .......... 94%  954G 1s
240550K .......... .......... .......... .......... .......... 94%  154M 1s
240600K .......... .......... .......... .......... .......... 94%  341M 1s
240650K .......... .......... .......... .......... .......... 94%  266M 1s
240700K .......... .......... .......... .......... .......... 94%  224M 1s
240750K .......... .......... .......... .......... .......... 94%  954G 1s
240800K .......... .......... .......... .......... .......... 94%  242M 1s
240850K .......... .......... .......... .......... .......... 94%  393M 1s
240900K .......... .......... .......... .......... .......... 94%  241M 1s
240950K .......... .......... .......... .......... .......... 94%  284M 1s
241000K .......... .......... .......... .......... .......... 94%  954G 1s
241050K .......... .......... .......... .......... .......... 94% 31,1M 1s
241100K .......... .......... .......... .......... .......... 94% 33,9M 1s
241150K .......... .......... .......... .......... .......... 94% 24,3M 1s
241200K .......... .......... .......... .......... .......... 94% 18,5M 1s
241250K .......... .......... .......... .......... .......... 94% 23,0M 1s
241300K .......... .......... .......... .......... .......... 94% 13,4M 1s
241350K .......... .......... .......... .......... .......... 94% 18,7M 1s
241400K .......... .......... .......... .......... .......... 94% 23,9M 1s
241450K .......... .......... .......... .......... .......... 94%  954G 1s
241500K .......... .......... .......... .......... .......... 94% 24,6M 1s
241550K .......... .......... .......... .......... .......... 94% 26,3M 1s
241600K .......... .......... .......... .......... .......... 94% 30,1M 1s
241650K .......... .......... .......... .......... .......... 94% 36,1M 1s
241700K .......... .......... .......... .......... .......... 94% 23,7M 1s
241750K .......... .......... .......... .......... .......... 94% 63,2M 1s
241800K .......... .......... .......... .......... .......... 94% 36,8M 1s
241850K .......... .......... .......... .......... .......... 94% 46,0M 1s
241900K .......... .......... .......... .......... .......... 94% 26,6M 1s
241950K .......... .......... .......... .......... .......... 94% 37,2M 1s
242000K .......... .......... .......... .......... .......... 94% 15,3M 1s
242050K .......... .......... .......... .......... .......... 94% 30,0M 1s
242100K .......... .......... .......... .......... .......... 94% 12,3M 1s
242150K .......... .......... .......... .......... .......... 94% 51,6M 1s
242200K .......... .......... .......... .......... .......... 94% 32,8M 1s
242250K .......... .......... .......... .......... .......... 94%  117M 1s
242300K .......... .......... .......... .......... .......... 94% 40,5M 1s
242350K .......... .......... .......... .......... .......... 94% 26,2M 1s
242400K .......... .......... .......... .......... .......... 95% 26,9M 1s
242450K .......... .......... .......... .......... .......... 95% 41,4M 1s
242500K .......... .......... .......... .......... .......... 95% 10,2M 1s
242550K .......... .......... .......... .......... .......... 95% 34,1M 1s
242600K .......... .......... .......... .......... .......... 95% 39,1M 1s
242650K .......... .......... .......... .......... .......... 95% 17,0M 1s
242700K .......... .......... .......... .......... .......... 95%  123M 1s
242750K .......... .......... .......... .......... .......... 95% 38,4M 1s
242800K .......... .......... .......... .......... .......... 95% 62,5M 1s
242850K .......... .......... .......... .......... .......... 95% 25,4M 1s
242900K .......... .......... .......... .......... .......... 95% 10,8M 1s
242950K .......... .......... .......... .......... .......... 95% 34,2M 1s
243000K .......... .......... .......... .......... .......... 95% 30,4M 1s
243050K .......... .......... .......... .......... .......... 95% 43,9M 1s
243100K .......... .......... .......... .......... .......... 95% 25,1M 1s
243150K .......... .......... .......... .......... .......... 95% 41,1M 1s
243200K .......... .......... .......... .......... .......... 95% 38,9M 1s
243250K .......... .......... .......... .......... .......... 95% 29,4M 1s
243300K .......... .......... .......... .......... .......... 95% 18,7M 1s
243350K .......... .......... .......... .......... .......... 95% 26,4M 1s
243400K .......... .......... .......... .......... .......... 95% 37,2M 1s
243450K .......... .......... .......... .......... .......... 95% 30,7M 1s
243500K .......... .......... .......... .......... .......... 95% 17,7M 1s
243550K .......... .......... .......... .......... .......... 95% 46,0M 1s
243600K .......... .......... .......... .......... .......... 95% 17,9M 1s
243650K .......... .......... .......... .......... .......... 95% 79,7M 1s
243700K .......... .......... .......... .......... .......... 95% 44,0M 1s
243750K .......... .......... .......... .......... .......... 95% 18,5M 1s
243800K .......... .......... .......... .......... .......... 95% 40,9M 1s
243850K .......... .......... .......... .......... .......... 95% 34,2M 1s
243900K .......... .......... .......... .......... .......... 95% 38,7M 0s
243950K .......... .......... .......... .......... .......... 95% 27,0M 0s
244000K .......... .......... .......... .......... .......... 95% 39,3M 0s
244050K .......... .......... .......... .......... .......... 95% 43,7M 0s
244100K .......... .......... .......... .......... .......... 95% 7,73M 0s
244150K .......... .......... .......... .......... .......... 95% 82,0M 0s
244200K .......... .......... .......... .......... .......... 95% 95,4M 0s
244250K .......... .......... .......... .......... .......... 95% 24,8M 0s
244300K .......... .......... .......... .......... .......... 95% 27,4M 0s
244350K .......... .......... .......... .......... .......... 95% 31,2M 0s
244400K .......... .......... .......... .......... .......... 95% 53,3M 0s
244450K .......... .......... .......... .......... .......... 95% 1,08M 0s
244500K .......... .......... .......... .......... .......... 95% 11,8M 0s
244550K .......... .......... .......... .......... .......... 95%  954G 0s
244600K .......... .......... .......... .......... .......... 95% 49,0M 0s
244650K .......... .......... .......... .......... .......... 95% 63,6M 0s
244700K .......... .......... .......... .......... .......... 95% 37,6M 0s
244750K .......... .......... .......... .......... .......... 95%  954G 0s
244800K .......... .......... .......... .......... .......... 95% 46,3M 0s
244850K .......... .......... .......... .......... .......... 95% 72,3M 0s
244900K .......... .......... .......... .......... .......... 95%  159M 0s
244950K .......... .......... .......... .......... .......... 96% 6,52M 0s
245000K .......... .......... .......... .......... .......... 96% 90,4M 0s
245050K .......... .......... .......... .......... .......... 96%  118M 0s
245100K .......... .......... .......... .......... .......... 96%  190M 0s
245150K .......... .......... .......... .......... .......... 96%  207M 0s
245200K .......... .......... .......... .......... .......... 96% 7,61M 0s
245250K .......... .......... .......... .......... .......... 96% 62,9M 0s
245300K .......... .......... .......... .......... .......... 96% 59,5M 0s
245350K .......... .......... .......... .......... .......... 96% 10,3M 0s
245400K .......... .......... .......... .......... .......... 96%  954G 0s
245450K .......... .......... .......... .......... .......... 96% 44,2M 0s
245500K .......... .......... .......... .......... .......... 96% 86,9M 0s
245550K .......... .......... .......... .......... .......... 96% 31,4M 0s
245600K .......... .......... .......... .......... .......... 96%  303M 0s
245650K .......... .......... .......... .......... .......... 96%  387M 0s
245700K .......... .......... .......... .......... .......... 96%  954G 0s
245750K .......... .......... .......... .......... .......... 96%  173M 0s
245800K .......... .......... .......... .......... .......... 96%  268M 0s
245850K .......... .......... .......... .......... .......... 96%  401M 0s
245900K .......... .......... .......... .......... .......... 96%  954G 0s
245950K .......... .......... .......... .......... .......... 96%  385M 0s
246000K .......... .......... .......... .......... .......... 96%  413M 0s
246050K .......... .......... .......... .......... .......... 96%  400M 0s
246100K .......... .......... .......... .......... .......... 96%  378M 0s
246150K .......... .......... .......... .......... .......... 96%  954G 0s
246200K .......... .......... .......... .......... .......... 96%  103M 0s
246250K .......... .......... .......... .......... .......... 96% 72,4M 0s
246300K .......... .......... .......... .......... .......... 96% 64,5M 0s
246350K .......... .......... .......... .......... .......... 96% 78,0M 0s
246400K .......... .......... .......... .......... .......... 96% 63,8M 0s
246450K .......... .......... .......... .......... .......... 96% 34,6M 0s
246500K .......... .......... .......... .......... .......... 96% 14,1M 0s
246550K .......... .......... .......... .......... .......... 96% 25,7M 0s
246600K .......... .......... .......... .......... .......... 96% 38,3M 0s
246650K .......... .......... .......... .......... .......... 96% 41,8M 0s
246700K .......... .......... .......... .......... .......... 96% 38,2M 0s
246750K .......... .......... .......... .......... .......... 96% 23,2M 0s
246800K .......... .......... .......... .......... .......... 96% 40,7M 0s
246850K .......... .......... .......... .......... .......... 96% 15,6M 0s
246900K .......... .......... .......... .......... .......... 96% 25,3M 0s
246950K .......... .......... .......... .......... .......... 96% 50,1M 0s
247000K .......... .......... .......... .......... .......... 96% 13,5M 0s
247050K .......... .......... .......... .......... .......... 96% 93,5M 0s
247100K .......... .......... .......... .......... .......... 96% 18,9M 0s
247150K .......... .......... .......... .......... .......... 96% 17,5M 0s
247200K .......... .......... .......... .......... .......... 96% 18,5M 0s
247250K .......... .......... .......... .......... .......... 96% 38,2M 0s
247300K .......... .......... .......... .......... .......... 96% 14,7M 0s
247350K .......... .......... .......... .......... .......... 96% 34,4M 0s
247400K .......... .......... .......... .......... .......... 96% 52,0M 0s
247450K .......... .......... .......... .......... .......... 96% 10,6M 0s
247500K .......... .......... .......... .......... .......... 97% 23,6M 0s
247550K .......... .......... .......... .......... .......... 97% 34,6M 0s
247600K .......... .......... .......... .......... .......... 97% 34,0M 0s
247650K .......... .......... .......... .......... .......... 97% 36,2M 0s
247700K .......... .......... .......... .......... .......... 97% 36,6M 0s
247750K .......... .......... .......... .......... .......... 97% 43,2M 0s
247800K .......... .......... .......... .......... .......... 97% 35,2M 0s
247850K .......... .......... .......... .......... .......... 97% 14,3M 0s
247900K .......... .......... .......... .......... .......... 97% 1,24M 0s
247950K .......... .......... .......... .......... .......... 97% 25,3M 0s
248000K .......... .......... .......... .......... .......... 97%  298M 0s
248050K .......... .......... .......... .......... .......... 97% 13,6M 0s
248100K .......... .......... .......... .......... .......... 97%  131M 0s
248150K .......... .......... .......... .......... .......... 97% 56,0M 0s
248200K .......... .......... .......... .......... .......... 97%  954G 0s
248250K .......... .......... .......... .......... .......... 97% 3,90M 0s
248300K .......... .......... .......... .......... .......... 97% 13,5M 0s
248350K .......... .......... .......... .......... .......... 97%  199M 0s
248400K .......... .......... .......... .......... .......... 97% 64,6M 0s
248450K .......... .......... .......... .......... .......... 97% 15,7M 0s
248500K .......... .......... .......... .......... .......... 97%  381M 0s
248550K .......... .......... .......... .......... .......... 97% 23,8M 0s
248600K .......... .......... .......... .......... .......... 97% 18,4M 0s
248650K .......... .......... .......... .......... .......... 97%  954G 0s
248700K .......... .......... .......... .......... .......... 97%  155M 0s
248750K .......... .......... .......... .......... .......... 97% 81,9M 0s
248800K .......... .......... .......... .......... .......... 97%  954G 0s
248850K .......... .......... .......... .......... .......... 97%  144M 0s
248900K .......... .......... .......... .......... .......... 97% 60,3M 0s
248950K .......... .......... .......... .......... .......... 97%  308M 0s
249000K .......... .......... .......... .......... .......... 97%  382M 0s
249050K .......... .......... .......... .......... .......... 97%  389M 0s
249100K .......... .......... .......... .......... .......... 97%  954G 0s
249150K .......... .......... .......... .......... .......... 97%  376M 0s
249200K .......... .......... .......... .......... .......... 97%  416M 0s
249250K .......... .......... .......... .......... .......... 97%  205M 0s
249300K .......... .......... .......... .......... .......... 97%  954G 0s
249350K .......... .......... .......... .......... .......... 97%  377M 0s
249400K .......... .......... .......... .......... .......... 97%  385M 0s
249450K .......... .......... .......... .......... .......... 97% 91,2M 0s
249500K .......... .......... .......... .......... .......... 97% 61,6M 0s
249550K .......... .......... .......... .......... .......... 97%  954G 0s
249600K .......... .......... .......... .......... .......... 97% 93,2M 0s
249650K .......... .......... .......... .......... .......... 97%  133M 0s
249700K .......... .......... .......... .......... .......... 97%  339M 0s
249750K .......... .......... .......... .......... .......... 97%  954G 0s
249800K .......... .......... .......... .......... .......... 97%  359M 0s
249850K .......... .......... .......... .......... .......... 97% 45,7M 0s
249900K .......... .......... .......... .......... .......... 97% 23,3M 0s
249950K .......... .......... .......... .......... .......... 97% 40,3M 0s
250000K .......... .......... .......... .......... .......... 97% 9,99M 0s
250050K .......... .......... .......... .......... .......... 98% 44,6M 0s
250100K .......... .......... .......... .......... .......... 98% 22,3M 0s
250150K .......... .......... .......... .......... .......... 98% 27,6M 0s
250200K .......... .......... .......... .......... .......... 98% 30,6M 0s
250250K .......... .......... .......... .......... .......... 98% 37,3M 0s
250300K .......... .......... .......... .......... .......... 98% 31,4M 0s
250350K .......... .......... .......... .......... .......... 98% 34,1M 0s
250400K .......... .......... .......... .......... .......... 98% 32,3M 0s
250450K .......... .......... .......... .......... .......... 98% 17,2M 0s
250500K .......... .......... .......... .......... .......... 98% 37,4M 0s
250550K .......... .......... .......... .......... .......... 98% 17,1M 0s
250600K .......... .......... .......... .......... .......... 98% 38,5M 0s
250650K .......... .......... .......... .......... .......... 98% 28,1M 0s
250700K .......... .......... .......... .......... .......... 98% 27,7M 0s
250750K .......... .......... .......... .......... .......... 98% 38,1M 0s
250800K .......... .......... .......... .......... .......... 98% 35,7M 0s
250850K .......... .......... .......... .......... .......... 98% 15,8M 0s
250900K .......... .......... .......... .......... .......... 98% 40,3M 0s
250950K .......... .......... .......... .......... .......... 98% 29,8M 0s
251000K .......... .......... .......... .......... .......... 98% 51,8M 0s
251050K .......... .......... .......... .......... .......... 98% 29,3M 0s
251100K .......... .......... .......... .......... .......... 98% 29,4M 0s
251150K .......... .......... .......... .......... .......... 98% 51,0M 0s
251200K .......... .......... .......... .......... .......... 98% 28,2M 0s
251250K .......... .......... .......... .......... .......... 98% 16,4M 0s
251300K .......... .......... .......... .......... .......... 98% 32,2M 0s
251350K .......... .......... .......... .......... .......... 98% 40,4M 0s
251400K .......... .......... .......... .......... .......... 98% 39,9M 0s
251450K .......... .......... .......... .......... .......... 98% 37,4M 0s
251500K .......... .......... .......... .......... .......... 98% 41,3M 0s
251550K .......... .......... .......... .......... .......... 98% 25,3M 0s
251600K .......... .......... .......... .......... .......... 98% 34,8M 0s
251650K .......... .......... .......... .......... .......... 98% 29,4M 0s
251700K .......... .......... .......... .......... .......... 98% 15,3M 0s
251750K .......... .......... .......... .......... .......... 98% 30,9M 0s
251800K .......... .......... .......... .......... .......... 98% 36,5M 0s
251850K .......... .......... .......... .......... .......... 98% 33,6M 0s
251900K .......... .......... .......... .......... .......... 98% 40,8M 0s
251950K .......... .......... .......... .......... .......... 98% 28,8M 0s
252000K .......... .......... .......... .......... .......... 98% 49,2M 0s
252050K .......... .......... .......... .......... .......... 98% 15,4M 0s
252100K .......... .......... .......... .......... .......... 98% 20,9M 0s
252150K .......... .......... .......... .......... .......... 98% 28,9M 0s
252200K .......... .......... .......... .......... .......... 98% 9,99M 0s
252250K .......... .......... .......... .......... .......... 98% 22,8M 0s
252300K .......... .......... .......... .......... .......... 98% 91,9M 0s
252350K .......... .......... .......... .......... .......... 98% 33,8M 0s
252400K .......... .......... .......... .......... .......... 98% 1,20M 0s
252450K .......... .......... .......... .......... .......... 98% 37,4M 0s
252500K .......... .......... .......... .......... .......... 98%  294M 0s
252550K .......... .......... .......... .......... .......... 98% 31,5M 0s
252600K .......... .......... .......... .......... .......... 99% 26,5M 0s
252650K .......... .......... .......... .......... .......... 99% 33,8M 0s
252700K .......... .......... .......... .......... .......... 99% 33,4M 0s
252750K .......... .......... .......... .......... .......... 99%  448M 0s
252800K .......... .......... .......... .......... .......... 99% 51,7M 0s
252850K .......... .......... .......... .......... .......... 99% 82,3M 0s
252900K .......... .......... .......... .......... .......... 99%  148M 0s
252950K .......... .......... .......... .......... .......... 99% 20,6M 0s
253000K .......... .......... .......... .......... .......... 99%  391M 0s
253050K .......... .......... .......... .......... .......... 99% 11,8M 0s
253100K .......... .......... .......... .......... .......... 99% 30,2M 0s
253150K .......... .......... .......... .......... .......... 99%  174M 0s
253200K .......... .......... .......... .......... .......... 99% 8,86M 0s
253250K .......... .......... .......... .......... .......... 99%  351M 0s
253300K .......... .......... .......... .......... .......... 99% 53,0M 0s
253350K .......... .......... .......... .......... .......... 99% 11,8M 0s
253400K .......... .......... .......... .......... .......... 99%  155M 0s
253450K .......... .......... .......... .......... .......... 99% 21,7M 0s
253500K .......... .......... .......... .......... .......... 99%  251M 0s
253550K .......... .......... .......... .......... .......... 99% 17,5M 0s
253600K .......... .......... .......... .......... .......... 99% 82,3M 0s
253650K .......... .......... .......... .......... .......... 99%  954G 0s
253700K .......... .......... .......... .......... .......... 99%  211M 0s
253750K .......... .......... .......... .......... .......... 99%  303M 0s
253800K .......... .......... .......... .......... .......... 99%  179M 0s
253850K .......... .......... .......... .......... .......... 99%  385M 0s
253900K .......... .......... .......... .......... .......... 99%  954G 0s
253950K .......... .......... .......... .......... .......... 99%  267M 0s
254000K .......... .......... .......... .......... .......... 99%  188M 0s
254050K .......... .......... .......... .......... .......... 99%  321M 0s
254100K .......... .......... .......... .......... .......... 99%  954G 0s
254150K .......... .......... .......... .......... .......... 99%  383M 0s
254200K .......... .......... .......... .......... .......... 99%  147M 0s
254250K .......... .......... .......... .......... .......... 99%  335M 0s
254300K .......... .......... .......... .......... .......... 99%  185M 0s
254350K .......... .......... .......... .......... .......... 99%  954G 0s
254400K .......... .......... .......... .......... .......... 99% 59,6M 0s
254450K .......... .......... .......... .......... .......... 99% 50,5M 0s
254500K .......... .......... .......... .......... .......... 99% 44,4M 0s
254550K .......... .......... .......... .......... .......... 99% 3,54M 0s
254600K .......... .......... .......... .......... .......... 99% 18,8M 0s
254650K .......... .......... .......... .......... .......... 99% 24,5M 0s
254700K .......... .......... .......... .......... .......... 99% 35,2M 0s
254750K .......... .......... .......... .......... .......... 99% 31,4M 0s
254800K .......... .......... .......... .......... .......... 99% 34,1M 0s
254850K .......... .......... .......... .......... .......... 99% 2,52M 0s
254900K .......... .......... .......... .......... .......... 99% 78,9M 0s
254950K .......... .......... .......... .......... .......... 99%  125M 0s
255000K .......... .......... .......... .......... .......... 99%  105M 0s
255050K .......... .......... .......... .......... .......... 99%  123M 0s
255100K .......... .......... .......... .......... .......... 99%  115M 0s
255150K .......... ........                                   100% 59,2M=11s

2023-12-10 21:45:07 (22,1 MB/s) - 'hotdog.zip' saved [261292301/261292301]

Archive:  hotdog.zip
   creating: hotdog/               
   creating: hotdog/train/         
   creating: hotdog/train/not-hotdog/
 extracting: hotdog/train/not-hotdog/50.png  
 extracting: hotdog/train/not-hotdog/554.png  
 extracting: hotdog/train/not-hotdog/299.png  
  inflating: hotdog/train/not-hotdog/428.png  
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  inflating: hotdog/train/not-hotdog/933.png  
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 extracting: hotdog/train/not-hotdog/728.png  
  inflating: hotdog/train/not-hotdog/667.png  
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  inflating: hotdog/train/not-hotdog/295.png  
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  inflating: hotdog/train/not-hotdog/400.png  
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 extracting: hotdog/train/not-hotdog/762.png  
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 extracting: hotdog/train/not-hotdog/137.png  
  inflating: hotdog/train/not-hotdog/472.png  
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  inflating: hotdog/train/not-hotdog/220.png  
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  inflating: hotdog/train/not-hotdog/996.png  
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 extracting: hotdog/train/not-hotdog/683.png  
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 extracting: hotdog/train/not-hotdog/592.png  
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 extracting: hotdog/train/not-hotdog/836.png  
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  inflating: hotdog/train/not-hotdog/189.png  
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 extracting: hotdog/train/not-hotdog/378.png  
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 extracting: hotdog/train/not-hotdog/165.png  
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 extracting: hotdog/train/not-hotdog/534.png  
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 extracting: hotdog/train/not-hotdog/434.png  
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 extracting: hotdog/train/not-hotdog/662.png  
 extracting: hotdog/train/not-hotdog/619.png  
 extracting: hotdog/train/not-hotdog/719.png  
 extracting: hotdog/train/not-hotdog/437.png  
  inflating: hotdog/train/not-hotdog/752.png  
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 extracting: hotdog/train/not-hotdog/83.png  
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 extracting: hotdog/train/not-hotdog/452.png  
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 extracting: hotdog/train/not-hotdog/163.png  
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 extracting: hotdog/train/not-hotdog/703.png  
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 extracting: hotdog/train/not-hotdog/262.png  
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 extracting: hotdog/train/not-hotdog/893.png  
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 extracting: hotdog/train/not-hotdog/157.png  
 extracting: hotdog/train/not-hotdog/102.png  
  inflating: hotdog/train/not-hotdog/612.png  
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 extracting: hotdog/train/not-hotdog/799.png  
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 extracting: hotdog/train/not-hotdog/748.png  
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 extracting: hotdog/train/not-hotdog/77.png  
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 extracting: hotdog/train/not-hotdog/192.png  
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 extracting: hotdog/train/not-hotdog/445.png  
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 extracting: hotdog/train/not-hotdog/187.png  
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 extracting: hotdog/train/not-hotdog/972.png  
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 extracting: hotdog/train/not-hotdog/283.png  
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  inflating: hotdog/train/not-hotdog/705.png  
 extracting: hotdog/train/not-hotdog/850.png  
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 extracting: hotdog/train/not-hotdog/453.png  
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 extracting: hotdog/train/not-hotdog/813.png  
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 extracting: hotdog/train/not-hotdog/919.png  
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 extracting: hotdog/train/not-hotdog/532.png  
 extracting: hotdog/train/not-hotdog/580.png  
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 extracting: hotdog/train/not-hotdog/951.png  
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  inflating: hotdog/train/not-hotdog/672.png  
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  inflating: hotdog/train/not-hotdog/376.png  
 extracting: hotdog/train/not-hotdog/291.png  
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 extracting: hotdog/train/not-hotdog/530.png  
 extracting: hotdog/train/not-hotdog/9.png  
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 extracting: hotdog/train/not-hotdog/430.png  
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  inflating: hotdog/train/not-hotdog/981.png  
 extracting: hotdog/train/not-hotdog/49.png  
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 extracting: hotdog/train/not-hotdog/946.png  
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 extracting: hotdog/train/not-hotdog/323.png  
  inflating: hotdog/train/not-hotdog/466.png  
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 extracting: hotdog/train/not-hotdog/495.png  
 extracting: hotdog/train/not-hotdog/840.png  
 extracting: hotdog/train/not-hotdog/281.png  
  inflating: hotdog/train/not-hotdog/586.png  
 extracting: hotdog/train/not-hotdog/990.png  
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  inflating: hotdog/train/not-hotdog/969.png  
  inflating: hotdog/train/not-hotdog/330.png  
 extracting: hotdog/train/not-hotdog/602.png  
 extracting: hotdog/train/not-hotdog/74.png  
 extracting: hotdog/train/not-hotdog/921.png  
  inflating: hotdog/train/not-hotdog/848.png  
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  inflating: hotdog/train/not-hotdog/721.png  
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  inflating: hotdog/train/not-hotdog/467.png  
 extracting: hotdog/train/not-hotdog/812.png  
 extracting: hotdog/train/not-hotdog/746.png  
  inflating: hotdog/train/not-hotdog/493.png  
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  inflating: hotdog/train/not-hotdog/23.png  
 extracting: hotdog/train/not-hotdog/559.png  
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 extracting: hotdog/train/not-hotdog/179.png  
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 extracting: hotdog/train/not-hotdog/716.png  
  inflating: hotdog/train/not-hotdog/999.png  
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 extracting: hotdog/train/not-hotdog/364.png  
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 extracting: hotdog/train/not-hotdog/185.png  
 extracting: hotdog/train/not-hotdog/843.png  
 extracting: hotdog/train/not-hotdog/141.png  
 extracting: hotdog/train/not-hotdog/190.png  
  inflating: hotdog/train/not-hotdog/726.png  
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 extracting: hotdog/train/not-hotdog/516.png  
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 extracting: hotdog/train/not-hotdog/382.png  
 extracting: hotdog/train/not-hotdog/655.png  
 extracting: hotdog/train/not-hotdog/222.png  
  inflating: hotdog/train/not-hotdog/154.png  
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 extracting: hotdog/train/not-hotdog/194.png  
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 extracting: hotdog/train/not-hotdog/19.png  
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 extracting: hotdog/train/not-hotdog/198.png  
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 extracting: hotdog/train/not-hotdog/65.png  
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 extracting: hotdog/train/not-hotdog/518.png  
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 extracting: hotdog/train/not-hotdog/790.png  
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 extracting: hotdog/train/not-hotdog/392.png  
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 extracting: hotdog/train/not-hotdog/815.png  
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 extracting: hotdog/train/not-hotdog/350.png  
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 extracting: hotdog/train/not-hotdog/75.png  
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 extracting: hotdog/train/not-hotdog/788.png  
 extracting: hotdog/train/not-hotdog/763.png  
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 extracting: hotdog/train/not-hotdog/732.png  
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 extracting: hotdog/train/not-hotdog/771.png  
 extracting: hotdog/train/not-hotdog/715.png  
  inflating: hotdog/train/not-hotdog/436.png  
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 extracting: hotdog/train/not-hotdog/290.png  
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 extracting: hotdog/train/not-hotdog/431.png  
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  inflating: hotdog/train/not-hotdog/853.png  
  inflating: hotdog/train/not-hotdog/831.png  
 extracting: hotdog/train/not-hotdog/101.png  
 extracting: hotdog/train/not-hotdog/383.png  
  inflating: hotdog/train/not-hotdog/22.png  
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 extracting: hotdog/train/not-hotdog/839.png  
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 extracting: hotdog/train/not-hotdog/877.png  
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 extracting: hotdog/train/not-hotdog/264.png  
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 extracting: hotdog/train/not-hotdog/675.png  
 extracting: hotdog/train/not-hotdog/345.png  
  inflating: hotdog/train/not-hotdog/0.png  
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 extracting: hotdog/train/not-hotdog/977.png  
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 extracting: hotdog/train/not-hotdog/355.png  
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 extracting: hotdog/train/not-hotdog/773.png  
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 extracting: hotdog/train/not-hotdog/663.png  
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 extracting: hotdog/train/not-hotdog/637.png  
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 extracting: hotdog/train/not-hotdog/650.png  
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 extracting: hotdog/train/not-hotdog/638.png  
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 extracting: hotdog/train/not-hotdog/415.png  
  inflating: hotdog/train/not-hotdog/100.png  
 extracting: hotdog/train/not-hotdog/635.png  
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 extracting: hotdog/train/not-hotdog/67.png  
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 extracting: hotdog/train/not-hotdog/507.png  
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  inflating: hotdog/train/not-hotdog/435.png  
  inflating: hotdog/train/not-hotdog/7.png  
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 extracting: hotdog/train/not-hotdog/98.png  
 extracting: hotdog/train/not-hotdog/696.png  
 extracting: hotdog/train/not-hotdog/531.png  
  inflating: hotdog/train/not-hotdog/451.png  
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 extracting: hotdog/train/not-hotdog/968.png  
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 extracting: hotdog/train/not-hotdog/104.png  
  inflating: hotdog/train/not-hotdog/391.png  
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  inflating: hotdog/train/not-hotdog/666.png  
 extracting: hotdog/train/not-hotdog/253.png  
 extracting: hotdog/train/not-hotdog/41.png  
 extracting: hotdog/train/not-hotdog/306.png  
 extracting: hotdog/train/not-hotdog/58.png  
  inflating: hotdog/train/not-hotdog/93.png  
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  inflating: hotdog/train/not-hotdog/240.png  
 extracting: hotdog/train/not-hotdog/874.png  
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 extracting: hotdog/train/not-hotdog/739.png  
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 extracting: hotdog/train/not-hotdog/471.png  
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 extracting: hotdog/train/not-hotdog/514.png  
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 extracting: hotdog/train/not-hotdog/669.png  
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 extracting: hotdog/train/not-hotdog/331.png  
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 extracting: hotdog/train/not-hotdog/125.png  
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 extracting: hotdog/train/not-hotdog/706.png  
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 extracting: hotdog/train/not-hotdog/865.png  
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 extracting: hotdog/train/not-hotdog/869.png  
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 extracting: hotdog/train/not-hotdog/427.png  
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 extracting: hotdog/train/not-hotdog/520.png  
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 extracting: hotdog/train/not-hotdog/727.png  
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 extracting: hotdog/train/not-hotdog/960.png  
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 extracting: hotdog/train/not-hotdog/529.png  
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 extracting: hotdog/train/not-hotdog/324.png  
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 extracting: hotdog/train/not-hotdog/652.png  
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 extracting: hotdog/train/not-hotdog/252.png  
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 extracting: hotdog/train/not-hotdog/888.png  
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 extracting: hotdog/train/not-hotdog/86.png  
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 extracting: hotdog/train/not-hotdog/700.png  
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 extracting: hotdog/train/not-hotdog/861.png  
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 extracting: hotdog/train/not-hotdog/633.png  
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  inflating: hotdog/train/not-hotdog/352.png  
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  inflating: hotdog/train/not-hotdog/689.png  
 extracting: hotdog/train/not-hotdog/164.png  
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 extracting: hotdog/train/not-hotdog/765.png  
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 extracting: hotdog/train/not-hotdog/631.png  
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 extracting: hotdog/train/not-hotdog/535.png  
 extracting: hotdog/train/not-hotdog/176.png  
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 extracting: hotdog/train/not-hotdog/52.png  
 extracting: hotdog/train/not-hotdog/265.png  
  inflating: hotdog/train/not-hotdog/792.png  
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 extracting: hotdog/train/not-hotdog/970.png  
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 extracting: hotdog/train/not-hotdog/841.png  
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 extracting: hotdog/train/not-hotdog/105.png  
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 extracting: hotdog/train/not-hotdog/731.png  
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 extracting: hotdog/train/not-hotdog/108.png  
 extracting: hotdog/train/not-hotdog/938.png  
  inflating: hotdog/train/not-hotdog/151.png  
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 extracting: hotdog/train/not-hotdog/976.png  
 extracting: hotdog/train/not-hotdog/844.png  
 extracting: hotdog/train/not-hotdog/476.png  
  inflating: hotdog/train/not-hotdog/99.png  
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 extracting: hotdog/train/not-hotdog/78.png  
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 extracting: hotdog/train/not-hotdog/439.png  
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 extracting: hotdog/train/not-hotdog/159.png  
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 extracting: hotdog/train/not-hotdog/103.png  
 extracting: hotdog/train/not-hotdog/208.png  
  inflating: hotdog/train/not-hotdog/5.png  
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 extracting: hotdog/train/not-hotdog/915.png  
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 extracting: hotdog/train/not-hotdog/745.png  
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 extracting: hotdog/train/not-hotdog/82.png  
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 extracting: hotdog/train/not-hotdog/860.png  
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  inflating: hotdog/train/not-hotdog/626.png  
  inflating: hotdog/train/not-hotdog/794.png  
 extracting: hotdog/train/not-hotdog/697.png  
 extracting: hotdog/train/not-hotdog/407.png  
 extracting: hotdog/train/not-hotdog/842.png  
  inflating: hotdog/train/not-hotdog/922.png  
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  inflating: hotdog/train/not-hotdog/223.png  
  inflating: hotdog/train/not-hotdog/522.png  
   creating: hotdog/train/hotdog/  
  inflating: hotdog/train/hotdog/50.png  
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 extracting: hotdog/train/hotdog/284.png  
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 extracting: hotdog/train/hotdog/295.png  
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 extracting: hotdog/train/hotdog/343.png  
 extracting: hotdog/train/hotdog/399.png  
  inflating: hotdog/train/hotdog/618.png  
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 extracting: hotdog/train/hotdog/231.png  
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  inflating: hotdog/train/hotdog/239.png  
 extracting: hotdog/train/hotdog/606.png  
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 extracting: hotdog/train/hotdog/560.png  
  inflating: hotdog/train/hotdog/334.png  
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 extracting: hotdog/train/hotdog/829.png  
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 extracting: hotdog/train/hotdog/312.png  
  inflating: hotdog/train/hotdog/762.png  
  inflating: hotdog/train/hotdog/789.png  
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 extracting: hotdog/train/hotdog/472.png  
  inflating: hotdog/train/hotdog/995.png  
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  inflating: hotdog/train/hotdog/389.png  
  inflating: hotdog/train/hotdog/971.png  
 extracting: hotdog/train/hotdog/607.png  
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  inflating: hotdog/train/hotdog/936.png  
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  inflating: hotdog/train/hotdog/220.png  
  inflating: hotdog/train/hotdog/747.png  
 extracting: hotdog/train/hotdog/97.png  
 extracting: hotdog/train/hotdog/126.png  
  inflating: hotdog/train/hotdog/996.png  
 extracting: hotdog/train/hotdog/327.png  
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  inflating: hotdog/train/hotdog/967.png  
  inflating: hotdog/train/hotdog/683.png  
 extracting: hotdog/train/hotdog/952.png  
 extracting: hotdog/train/hotdog/776.png  
  inflating: hotdog/train/hotdog/592.png  
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  inflating: hotdog/train/hotdog/490.png  
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 extracting: hotdog/train/hotdog/269.png  
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  inflating: hotdog/train/hotdog/993.png  
  inflating: hotdog/train/hotdog/4.png  
 extracting: hotdog/train/hotdog/796.png  
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  inflating: hotdog/train/hotdog/509.png  
  inflating: hotdog/train/hotdog/150.png  
  inflating: hotdog/train/hotdog/196.png  
 extracting: hotdog/train/hotdog/534.png  
 extracting: hotdog/train/hotdog/642.png  
  inflating: hotdog/train/hotdog/152.png  
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 extracting: hotdog/train/hotdog/953.png  
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 extracting: hotdog/train/hotdog/682.png  
  inflating: hotdog/train/hotdog/595.png  
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  inflating: hotdog/train/hotdog/619.png  
  inflating: hotdog/train/hotdog/719.png  
 extracting: hotdog/train/hotdog/437.png  
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  inflating: hotdog/train/hotdog/115.png  
 extracting: hotdog/train/hotdog/163.png  
  inflating: hotdog/train/hotdog/395.png  
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 extracting: hotdog/train/hotdog/772.png  
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 extracting: hotdog/train/hotdog/88.png  
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  inflating: hotdog/train/hotdog/741.png  
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 extracting: hotdog/train/hotdog/181.png  
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 extracting: hotdog/train/hotdog/561.png  
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 extracting: hotdog/train/hotdog/640.png  
  inflating: hotdog/train/hotdog/76.png  
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  inflating: hotdog/train/hotdog/799.png  
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  inflating: hotdog/train/hotdog/748.png  
 extracting: hotdog/train/hotdog/940.png  
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 extracting: hotdog/train/hotdog/229.png  
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 extracting: hotdog/train/hotdog/927.png  
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 extracting: hotdog/train/hotdog/501.png  
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 extracting: hotdog/train/hotdog/850.png  
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 extracting: hotdog/train/hotdog/924.png  
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 extracting: hotdog/train/hotdog/939.png  
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 extracting: hotdog/train/hotdog/513.png  
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 extracting: hotdog/train/hotdog/722.png  
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 extracting: hotdog/train/hotdog/168.png  
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 extracting: hotdog/train/hotdog/401.png  
 extracting: hotdog/train/hotdog/648.png  
 extracting: hotdog/train/hotdog/430.png  
  inflating: hotdog/train/hotdog/255.png  
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 extracting: hotdog/train/hotdog/649.png  
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 extracting: hotdog/train/hotdog/641.png  
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 extracting: hotdog/train/hotdog/568.png  
 extracting: hotdog/train/hotdog/575.png  
 extracting: hotdog/train/hotdog/969.png  
  inflating: hotdog/train/hotdog/330.png  
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 extracting: hotdog/train/hotdog/74.png  
 extracting: hotdog/train/hotdog/921.png  
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 extracting: hotdog/train/hotdog/721.png  
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 extracting: hotdog/train/hotdog/120.png  
 extracting: hotdog/train/hotdog/449.png  
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 extracting: hotdog/train/hotdog/45.png  
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 extracting: hotdog/train/hotdog/185.png  
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 extracting: hotdog/train/hotdog/726.png  
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 extracting: hotdog/train/hotdog/533.png  
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 extracting: hotdog/train/hotdog/154.png  
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 extracting: hotdog/train/hotdog/852.png  
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 extracting: hotdog/train/hotdog/632.png  
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 extracting: hotdog/train/hotdog/198.png  
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 extracting: hotdog/train/hotdog/962.png  
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 extracting: hotdog/train/hotdog/959.png  
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 extracting: hotdog/train/hotdog/900.png  
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 extracting: hotdog/train/hotdog/859.png  
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 extracting: hotdog/train/hotdog/877.png  
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 extracting: hotdog/train/hotdog/675.png  
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 extracting: hotdog/train/hotdog/742.png  
 extracting: hotdog/train/hotdog/296.png  
 extracting: hotdog/train/hotdog/879.png  
 extracting: hotdog/train/hotdog/977.png  
  inflating: hotdog/train/hotdog/707.png  
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 extracting: hotdog/train/hotdog/724.png  
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 extracting: hotdog/train/hotdog/415.png  
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 extracting: hotdog/train/hotdog/435.png  
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 extracting: hotdog/train/hotdog/696.png  
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 extracting: hotdog/train/hotdog/451.png  
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 extracting: hotdog/train/hotdog/968.png  
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 extracting: hotdog/train/hotdog/666.png  
 extracting: hotdog/train/hotdog/253.png  
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 extracting: hotdog/train/hotdog/551.png  
 extracting: hotdog/train/hotdog/643.png  
  inflating: hotdog/train/hotdog/240.png  
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 extracting: hotdog/train/hotdog/739.png  
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 extracting: hotdog/train/hotdog/627.png  
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 extracting: hotdog/train/hotdog/183.png  
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 extracting: hotdog/train/hotdog/29.png  
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 extracting: hotdog/train/hotdog/567.png  
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 extracting: hotdog/train/hotdog/943.png  
 extracting: hotdog/train/hotdog/473.png  
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 extracting: hotdog/train/hotdog/966.png  
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 extracting: hotdog/train/hotdog/320.png  
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 extracting: hotdog/train/hotdog/613.png  
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 extracting: hotdog/train/hotdog/471.png  
 extracting: hotdog/train/hotdog/579.png  
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 extracting: hotdog/train/hotdog/410.png  
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 extracting: hotdog/train/hotdog/170.png  
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 extracting: hotdog/train/hotdog/228.png  
 extracting: hotdog/train/hotdog/169.png  
 extracting: hotdog/train/hotdog/458.png  
  inflating: hotdog/train/hotdog/549.png  
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 extracting: hotdog/train/hotdog/234.png  
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 extracting: hotdog/train/hotdog/85.png  
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 extracting: hotdog/train/hotdog/851.png  
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 extracting: hotdog/train/hotdog/692.png  
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 extracting: hotdog/train/hotdog/582.png  
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 extracting: hotdog/train/hotdog/882.png  
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 extracting: hotdog/train/hotdog/331.png  
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 extracting: hotdog/train/hotdog/204.png  
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 extracting: hotdog/train/hotdog/870.png  
 extracting: hotdog/train/hotdog/365.png  
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 extracting: hotdog/train/hotdog/125.png  
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 extracting: hotdog/train/hotdog/923.png  
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 extracting: hotdog/train/hotdog/235.png  
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 extracting: hotdog/train/hotdog/727.png  
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 extracting: hotdog/train/hotdog/785.png  
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 extracting: hotdog/train/hotdog/738.png  
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 extracting: hotdog/train/hotdog/21.png  
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 extracting: hotdog/train/hotdog/896.png  
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 extracting: hotdog/train/hotdog/576.png  
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 extracting: hotdog/train/hotdog/985.png  
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 extracting: hotdog/train/hotdog/461.png  
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 extracting: hotdog/train/hotdog/770.png  
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 extracting: hotdog/train/hotdog/374.png  
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 extracting: hotdog/train/hotdog/885.png  
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 extracting: hotdog/train/hotdog/925.png  
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 extracting: hotdog/train/hotdog/577.png  
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 extracting: hotdog/train/hotdog/688.png  
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 extracting: hotdog/train/hotdog/13.png  
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 extracting: hotdog/train/hotdog/787.png  
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 extracting: hotdog/train/hotdog/711.png  
 extracting: hotdog/train/hotdog/214.png  
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 extracting: hotdog/train/hotdog/340.png  
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 extracting: hotdog/train/hotdog/601.png  
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 extracting: hotdog/train/hotdog/750.png  
 extracting: hotdog/train/hotdog/508.png  
  inflating: hotdog/train/hotdog/810.png  
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 extracting: hotdog/train/hotdog/630.png  
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 extracting: hotdog/train/hotdog/845.png  
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 extracting: hotdog/train/hotdog/164.png  
 extracting: hotdog/train/hotdog/623.png  
  inflating: hotdog/train/hotdog/46.png  
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 extracting: hotdog/train/hotdog/631.png  
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 extracting: hotdog/train/hotdog/766.png  
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  inflating: hotdog/train/hotdog/907.png  
 extracting: hotdog/train/hotdog/975.png  
 extracting: hotdog/train/hotdog/535.png  
  inflating: hotdog/train/hotdog/176.png  
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 extracting: hotdog/train/hotdog/265.png  
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 extracting: hotdog/train/hotdog/203.png  
 extracting: hotdog/train/hotdog/970.png  
 extracting: hotdog/train/hotdog/625.png  
  inflating: hotdog/train/hotdog/729.png  
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 extracting: hotdog/train/hotdog/286.png  
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 extracting: hotdog/train/hotdog/710.png  
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 extracting: hotdog/train/hotdog/844.png  
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  inflating: hotdog/train/hotdog/855.png  
  inflating: hotdog/train/hotdog/369.png  
 extracting: hotdog/train/hotdog/647.png  
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 extracting: hotdog/train/hotdog/916.png  
  inflating: hotdog/train/hotdog/564.png  
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  inflating: hotdog/train/hotdog/610.png  
  inflating: hotdog/train/hotdog/903.png  
 extracting: hotdog/train/hotdog/318.png  
  inflating: hotdog/train/hotdog/676.png  
  inflating: hotdog/train/hotdog/78.png  
 extracting: hotdog/train/hotdog/260.png  
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  inflating: hotdog/train/hotdog/659.png  
  inflating: hotdog/train/hotdog/87.png  
 extracting: hotdog/train/hotdog/590.png  
 extracting: hotdog/train/hotdog/932.png  
  inflating: hotdog/train/hotdog/487.png  
 extracting: hotdog/train/hotdog/230.png  
  inflating: hotdog/train/hotdog/159.png  
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  inflating: hotdog/train/hotdog/103.png  
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 extracting: hotdog/train/hotdog/5.png  
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 extracting: hotdog/train/hotdog/95.png  
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  inflating: hotdog/train/hotdog/915.png  
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 extracting: hotdog/train/hotdog/745.png  
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 extracting: hotdog/train/hotdog/860.png  
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 extracting: hotdog/train/hotdog/626.png  
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 extracting: hotdog/train/hotdog/697.png  
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 extracting: hotdog/train/hotdog/922.png  
 extracting: hotdog/train/hotdog/450.png  
  inflating: hotdog/train/hotdog/553.png  
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  inflating: hotdog/train/hotdog/510.png  
  inflating: hotdog/train/hotdog/223.png  
  inflating: hotdog/train/hotdog/522.png  
   creating: hotdog/test/          
   creating: hotdog/test/not-hotdog/
  inflating: hotdog/test/not-hotdog/1379.png  
  inflating: hotdog/test/not-hotdog/1388.png  
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 extracting: hotdog/test/not-hotdog/1383.png  
  inflating: hotdog/test/not-hotdog/1377.png  
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  inflating: hotdog/test/not-hotdog/1200.png  
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 extracting: hotdog/test/not-hotdog/1206.png  
 extracting: hotdog/test/not-hotdog/1246.png  
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 extracting: hotdog/test/not-hotdog/1297.png  
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 extracting: hotdog/test/not-hotdog/1089.png  
 extracting: hotdog/test/not-hotdog/1033.png  
 extracting: hotdog/test/not-hotdog/1205.png  
  inflating: hotdog/test/not-hotdog/1073.png  
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  inflating: hotdog/test/not-hotdog/1024.png  
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 extracting: hotdog/test/not-hotdog/1048.png  
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 extracting: hotdog/test/not-hotdog/1060.png  
 extracting: hotdog/test/not-hotdog/1203.png  
  inflating: hotdog/test/not-hotdog/1090.png  
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 extracting: hotdog/test/not-hotdog/1267.png  
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 extracting: hotdog/test/not-hotdog/1182.png  
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 extracting: hotdog/test/not-hotdog/1035.png  
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 extracting: hotdog/test/not-hotdog/1005.png  
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  inflating: hotdog/test/not-hotdog/1038.png  
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 extracting: hotdog/test/not-hotdog/1254.png  
 extracting: hotdog/test/not-hotdog/1291.png  
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 extracting: hotdog/test/not-hotdog/1154.png  
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  inflating: hotdog/test/not-hotdog/1087.png  
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 extracting: hotdog/test/not-hotdog/1056.png  
  inflating: hotdog/test/not-hotdog/1289.png  
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  inflating: hotdog/test/not-hotdog/1107.png  
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 extracting: hotdog/test/not-hotdog/1264.png  
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 extracting: hotdog/test/not-hotdog/1120.png  
 extracting: hotdog/test/not-hotdog/1226.png  
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  inflating: hotdog/test/not-hotdog/1083.png  
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  inflating: hotdog/test/not-hotdog/1081.png  
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  inflating: hotdog/test/not-hotdog/1337.png  
  inflating: hotdog/test/not-hotdog/1225.png  
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 extracting: hotdog/test/not-hotdog/1308.png  
 extracting: hotdog/test/not-hotdog/1214.png  
  inflating: hotdog/test/not-hotdog/1037.png  
  inflating: hotdog/test/not-hotdog/1386.png  
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  inflating: hotdog/test/not-hotdog/1318.png  
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  inflating: hotdog/test/not-hotdog/1020.png  
  inflating: hotdog/test/not-hotdog/1325.png  
  inflating: hotdog/test/not-hotdog/1238.png  
  inflating: hotdog/test/not-hotdog/1364.png  
  inflating: hotdog/test/not-hotdog/1098.png  
 extracting: hotdog/test/not-hotdog/1298.png  
 extracting: hotdog/test/not-hotdog/1296.png  
  inflating: hotdog/test/not-hotdog/1153.png  
  inflating: hotdog/test/not-hotdog/1025.png  
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  inflating: hotdog/test/not-hotdog/1117.png  
 extracting: hotdog/test/not-hotdog/1062.png  
  inflating: hotdog/test/not-hotdog/1017.png  
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 extracting: hotdog/test/not-hotdog/1011.png  
  inflating: hotdog/test/not-hotdog/1273.png  
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 extracting: hotdog/test/not-hotdog/1122.png  
  inflating: hotdog/test/not-hotdog/1346.png  
  inflating: hotdog/test/not-hotdog/1134.png  
  inflating: hotdog/test/not-hotdog/1115.png  
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 extracting: hotdog/test/not-hotdog/1270.png  
  inflating: hotdog/test/not-hotdog/1084.png  
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  inflating: hotdog/test/not-hotdog/1269.png  
  inflating: hotdog/test/not-hotdog/1330.png  
  inflating: hotdog/test/not-hotdog/1189.png  
  inflating: hotdog/test/not-hotdog/1022.png  
  inflating: hotdog/test/not-hotdog/1173.png  
 extracting: hotdog/test/not-hotdog/1288.png  
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 extracting: hotdog/test/not-hotdog/1256.png  
  inflating: hotdog/test/not-hotdog/1343.png  
  inflating: hotdog/test/not-hotdog/1193.png  
  inflating: hotdog/test/not-hotdog/1103.png  
  inflating: hotdog/test/not-hotdog/1333.png  
 extracting: hotdog/test/not-hotdog/1204.png  
  inflating: hotdog/test/not-hotdog/1194.png  
  inflating: hotdog/test/not-hotdog/1008.png  
 extracting: hotdog/test/not-hotdog/1215.png  
  inflating: hotdog/test/not-hotdog/1295.png  
  inflating: hotdog/test/not-hotdog/1150.png  
  inflating: hotdog/test/not-hotdog/1242.png  
  inflating: hotdog/test/not-hotdog/1210.png  
  inflating: hotdog/test/not-hotdog/1396.png  
  inflating: hotdog/test/not-hotdog/1055.png  
  inflating: hotdog/test/not-hotdog/1086.png  
  inflating: hotdog/test/not-hotdog/1258.png  
  inflating: hotdog/test/not-hotdog/1145.png  
  inflating: hotdog/test/not-hotdog/1338.png  
  inflating: hotdog/test/not-hotdog/1202.png  
  inflating: hotdog/test/not-hotdog/1353.png  
  inflating: hotdog/test/not-hotdog/1290.png  
 extracting: hotdog/test/not-hotdog/1132.png  
  inflating: hotdog/test/not-hotdog/1235.png  
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 extracting: hotdog/test/not-hotdog/1266.png  
  inflating: hotdog/test/not-hotdog/1023.png  
  inflating: hotdog/test/not-hotdog/1123.png  
  inflating: hotdog/test/not-hotdog/1163.png  
  inflating: hotdog/test/not-hotdog/1111.png  
  inflating: hotdog/test/not-hotdog/1057.png  
  inflating: hotdog/test/not-hotdog/1369.png  
 extracting: hotdog/test/not-hotdog/1331.png  
 extracting: hotdog/test/not-hotdog/1366.png  
 extracting: hotdog/test/not-hotdog/1237.png  
  inflating: hotdog/test/not-hotdog/1307.png  
  inflating: hotdog/test/not-hotdog/1313.png  
  inflating: hotdog/test/not-hotdog/1312.png  
  inflating: hotdog/test/not-hotdog/1126.png  
  inflating: hotdog/test/not-hotdog/1161.png  
  inflating: hotdog/test/not-hotdog/1003.png  
  inflating: hotdog/test/not-hotdog/1018.png  
  inflating: hotdog/test/not-hotdog/1280.png  
  inflating: hotdog/test/not-hotdog/1158.png  
  inflating: hotdog/test/not-hotdog/1128.png  
 extracting: hotdog/test/not-hotdog/1359.png  
  inflating: hotdog/test/not-hotdog/1341.png  
  inflating: hotdog/test/not-hotdog/1375.png  
 extracting: hotdog/test/not-hotdog/1149.png  
 extracting: hotdog/test/not-hotdog/1241.png  
 extracting: hotdog/test/not-hotdog/1094.png  
  inflating: hotdog/test/not-hotdog/1129.png  
  inflating: hotdog/test/not-hotdog/1332.png  
  inflating: hotdog/test/not-hotdog/1196.png  
  inflating: hotdog/test/not-hotdog/1004.png  
  inflating: hotdog/test/not-hotdog/1316.png  
  inflating: hotdog/test/not-hotdog/1231.png  
 extracting: hotdog/test/not-hotdog/1328.png  
  inflating: hotdog/test/not-hotdog/1174.png  
  inflating: hotdog/test/not-hotdog/1051.png  
  inflating: hotdog/test/not-hotdog/1207.png  
  inflating: hotdog/test/not-hotdog/1234.png  
  inflating: hotdog/test/not-hotdog/1125.png  
  inflating: hotdog/test/not-hotdog/1370.png  
  inflating: hotdog/test/not-hotdog/1054.png  
 extracting: hotdog/test/not-hotdog/1228.png  
  inflating: hotdog/test/not-hotdog/1109.png  
 extracting: hotdog/test/not-hotdog/1013.png  
 extracting: hotdog/test/not-hotdog/1240.png  
 extracting: hotdog/test/not-hotdog/1176.png  
  inflating: hotdog/test/not-hotdog/1216.png  
  inflating: hotdog/test/not-hotdog/1106.png  
  inflating: hotdog/test/not-hotdog/1159.png  
  inflating: hotdog/test/not-hotdog/1185.png  
 extracting: hotdog/test/not-hotdog/1064.png  
  inflating: hotdog/test/not-hotdog/1190.png  
 extracting: hotdog/test/not-hotdog/1066.png  
  inflating: hotdog/test/not-hotdog/1156.png  
  inflating: hotdog/test/not-hotdog/1192.png  
 extracting: hotdog/test/not-hotdog/1301.png  
  inflating: hotdog/test/not-hotdog/1255.png  
  inflating: hotdog/test/not-hotdog/1026.png  
  inflating: hotdog/test/not-hotdog/1110.png  
  inflating: hotdog/test/not-hotdog/1088.png  
 extracting: hotdog/test/not-hotdog/1180.png  
  inflating: hotdog/test/not-hotdog/1160.png  
  inflating: hotdog/test/not-hotdog/1282.png  
 extracting: hotdog/test/not-hotdog/1285.png  
 extracting: hotdog/test/not-hotdog/1032.png  
  inflating: hotdog/test/not-hotdog/1133.png  
  inflating: hotdog/test/not-hotdog/1049.png  
  inflating: hotdog/test/not-hotdog/1162.png  
 extracting: hotdog/test/not-hotdog/1151.png  
  inflating: hotdog/test/not-hotdog/1271.png  
  inflating: hotdog/test/not-hotdog/1006.png  
  inflating: hotdog/test/not-hotdog/1326.png  
  inflating: hotdog/test/not-hotdog/1143.png  
  inflating: hotdog/test/not-hotdog/1236.png  
 extracting: hotdog/test/not-hotdog/1272.png  
  inflating: hotdog/test/not-hotdog/1244.png  
  inflating: hotdog/test/not-hotdog/1367.png  
  inflating: hotdog/test/not-hotdog/1277.png  
 extracting: hotdog/test/not-hotdog/1381.png  
 extracting: hotdog/test/not-hotdog/1389.png  
  inflating: hotdog/test/not-hotdog/1372.png  
 extracting: hotdog/test/not-hotdog/1093.png  
 extracting: hotdog/test/not-hotdog/1069.png  
  inflating: hotdog/test/not-hotdog/1385.png  
  inflating: hotdog/test/not-hotdog/1209.png  
 extracting: hotdog/test/not-hotdog/1177.png  
  inflating: hotdog/test/not-hotdog/1324.png  
  inflating: hotdog/test/not-hotdog/1224.png  
  inflating: hotdog/test/not-hotdog/1100.png  
  inflating: hotdog/test/not-hotdog/1339.png  
 extracting: hotdog/test/not-hotdog/1148.png  
  inflating: hotdog/test/not-hotdog/1284.png  
  inflating: hotdog/test/not-hotdog/1208.png  
 extracting: hotdog/test/not-hotdog/1078.png  
 extracting: hotdog/test/not-hotdog/1334.png  
  inflating: hotdog/test/not-hotdog/1019.png  
  inflating: hotdog/test/not-hotdog/1141.png  
  inflating: hotdog/test/not-hotdog/1130.png  
 extracting: hotdog/test/not-hotdog/1265.png  
  inflating: hotdog/test/not-hotdog/1229.png  
  inflating: hotdog/test/not-hotdog/1175.png  
  inflating: hotdog/test/not-hotdog/1261.png  
  inflating: hotdog/test/not-hotdog/1157.png  
  inflating: hotdog/test/not-hotdog/1053.png  
  inflating: hotdog/test/not-hotdog/1152.png  
  inflating: hotdog/test/not-hotdog/1268.png  
  inflating: hotdog/test/not-hotdog/1350.png  
  inflating: hotdog/test/not-hotdog/1232.png  
 extracting: hotdog/test/not-hotdog/1021.png  
  inflating: hotdog/test/not-hotdog/1140.png  
  inflating: hotdog/test/not-hotdog/1230.png  
  inflating: hotdog/test/not-hotdog/1099.png  
  inflating: hotdog/test/not-hotdog/1104.png  
 extracting: hotdog/test/not-hotdog/1398.png  
 extracting: hotdog/test/not-hotdog/1075.png  
  inflating: hotdog/test/not-hotdog/1178.png  
  inflating: hotdog/test/not-hotdog/1260.png  
  inflating: hotdog/test/not-hotdog/1393.png  
  inflating: hotdog/test/not-hotdog/1102.png  
 extracting: hotdog/test/not-hotdog/1009.png  
  inflating: hotdog/test/not-hotdog/1321.png  
  inflating: hotdog/test/not-hotdog/1368.png  
  inflating: hotdog/test/not-hotdog/1233.png  
  inflating: hotdog/test/not-hotdog/1309.png  
  inflating: hotdog/test/not-hotdog/1147.png  
  inflating: hotdog/test/not-hotdog/1119.png  
  inflating: hotdog/test/not-hotdog/1016.png  
  inflating: hotdog/test/not-hotdog/1199.png  
 extracting: hotdog/test/not-hotdog/1001.png  
  inflating: hotdog/test/not-hotdog/1201.png  
  inflating: hotdog/test/not-hotdog/1293.png  
  inflating: hotdog/test/not-hotdog/1108.png  
  inflating: hotdog/test/not-hotdog/1071.png  
  inflating: hotdog/test/not-hotdog/1169.png  
  inflating: hotdog/test/not-hotdog/1058.png  
  inflating: hotdog/test/not-hotdog/1345.png  
 extracting: hotdog/test/not-hotdog/1068.png  
 extracting: hotdog/test/not-hotdog/1135.png  
  inflating: hotdog/test/not-hotdog/1211.png  
  inflating: hotdog/test/not-hotdog/1275.png  
  inflating: hotdog/test/not-hotdog/1336.png  
  inflating: hotdog/test/not-hotdog/1040.png  
  inflating: hotdog/test/not-hotdog/1142.png  
  inflating: hotdog/test/not-hotdog/1101.png  
  inflating: hotdog/test/not-hotdog/1197.png  
  inflating: hotdog/test/not-hotdog/1036.png  
  inflating: hotdog/test/not-hotdog/1170.png  
  inflating: hotdog/test/not-hotdog/1373.png  
  inflating: hotdog/test/not-hotdog/1082.png  
  inflating: hotdog/test/not-hotdog/1000.png  
  inflating: hotdog/test/not-hotdog/1171.png  
 extracting: hotdog/test/not-hotdog/1065.png  
  inflating: hotdog/test/not-hotdog/1349.png  
  inflating: hotdog/test/not-hotdog/1198.png  
  inflating: hotdog/test/not-hotdog/1222.png  
  inflating: hotdog/test/not-hotdog/1077.png  
  inflating: hotdog/test/not-hotdog/1335.png  
 extracting: hotdog/test/not-hotdog/1080.png  
  inflating: hotdog/test/not-hotdog/1091.png  
 extracting: hotdog/test/not-hotdog/1184.png  
  inflating: hotdog/test/not-hotdog/1327.png  
 extracting: hotdog/test/not-hotdog/1358.png  
 extracting: hotdog/test/not-hotdog/1061.png  
  inflating: hotdog/test/not-hotdog/1179.png  
  inflating: hotdog/test/not-hotdog/1329.png  
  inflating: hotdog/test/not-hotdog/1274.png  
  inflating: hotdog/test/not-hotdog/1344.png  
  inflating: hotdog/test/not-hotdog/1221.png  
  inflating: hotdog/test/not-hotdog/1374.png  
  inflating: hotdog/test/not-hotdog/1029.png  
  inflating: hotdog/test/not-hotdog/1395.png  
  inflating: hotdog/test/not-hotdog/1310.png  
  inflating: hotdog/test/not-hotdog/1397.png  
  inflating: hotdog/test/not-hotdog/1243.png  
  inflating: hotdog/test/not-hotdog/1292.png  
 extracting: hotdog/test/not-hotdog/1010.png  
  inflating: hotdog/test/not-hotdog/1187.png  
  inflating: hotdog/test/not-hotdog/1223.png  
 extracting: hotdog/test/not-hotdog/1041.png  
  inflating: hotdog/test/not-hotdog/1253.png  
  inflating: hotdog/test/not-hotdog/1168.png  
  inflating: hotdog/test/not-hotdog/1183.png  
  inflating: hotdog/test/not-hotdog/1382.png  
  inflating: hotdog/test/not-hotdog/1124.png  
  inflating: hotdog/test/not-hotdog/1097.png  
  inflating: hotdog/test/not-hotdog/1072.png  
   creating: hotdog/test/hotdog/   
  inflating: hotdog/test/hotdog/1379.png  
  inflating: hotdog/test/hotdog/1388.png  
 extracting: hotdog/test/hotdog/1067.png  
  inflating: hotdog/test/hotdog/1383.png  
  inflating: hotdog/test/hotdog/1377.png  
  inflating: hotdog/test/hotdog/1015.png  
  inflating: hotdog/test/hotdog/1172.png  
  inflating: hotdog/test/hotdog/1030.png  
  inflating: hotdog/test/hotdog/1114.png  
  inflating: hotdog/test/hotdog/1186.png  
  inflating: hotdog/test/hotdog/1200.png  
  inflating: hotdog/test/hotdog/1380.png  
 extracting: hotdog/test/hotdog/1247.png  
  inflating: hotdog/test/hotdog/1206.png  
  inflating: hotdog/test/hotdog/1246.png  
  inflating: hotdog/test/hotdog/1227.png  
  inflating: hotdog/test/hotdog/1079.png  
  inflating: hotdog/test/hotdog/1297.png  
  inflating: hotdog/test/hotdog/1378.png  
  inflating: hotdog/test/hotdog/1286.png  
  inflating: hotdog/test/hotdog/1045.png  
  inflating: hotdog/test/hotdog/1138.png  
  inflating: hotdog/test/hotdog/1299.png  
  inflating: hotdog/test/hotdog/1118.png  
  inflating: hotdog/test/hotdog/1047.png  
  inflating: hotdog/test/hotdog/1303.png  
  inflating: hotdog/test/hotdog/1089.png  
  inflating: hotdog/test/hotdog/1033.png  
  inflating: hotdog/test/hotdog/1205.png  
  inflating: hotdog/test/hotdog/1073.png  
  inflating: hotdog/test/hotdog/1305.png  
  inflating: hotdog/test/hotdog/1195.png  
 extracting: hotdog/test/hotdog/1371.png  
  inflating: hotdog/test/hotdog/1392.png  
  inflating: hotdog/test/hotdog/1024.png  
 extracting: hotdog/test/hotdog/1319.png  
  inflating: hotdog/test/hotdog/1287.png  
  inflating: hotdog/test/hotdog/1048.png  
  inflating: hotdog/test/hotdog/1155.png  
 extracting: hotdog/test/hotdog/1217.png  
  inflating: hotdog/test/hotdog/1060.png  
  inflating: hotdog/test/hotdog/1203.png  
  inflating: hotdog/test/hotdog/1090.png  
  inflating: hotdog/test/hotdog/1304.png  
 extracting: hotdog/test/hotdog/1063.png  
  inflating: hotdog/test/hotdog/1387.png  
  inflating: hotdog/test/hotdog/1267.png  
 extracting: hotdog/test/hotdog/1219.png  
 extracting: hotdog/test/hotdog/1182.png  
  inflating: hotdog/test/hotdog/1012.png  
  inflating: hotdog/test/hotdog/1139.png  
  inflating: hotdog/test/hotdog/1257.png  
  inflating: hotdog/test/hotdog/1281.png  
  inflating: hotdog/test/hotdog/1315.png  
  inflating: hotdog/test/hotdog/1028.png  
 extracting: hotdog/test/hotdog/1220.png  
  inflating: hotdog/test/hotdog/1116.png  
  inflating: hotdog/test/hotdog/1191.png  
  inflating: hotdog/test/hotdog/1188.png  
  inflating: hotdog/test/hotdog/1391.png  
  inflating: hotdog/test/hotdog/1034.png  
  inflating: hotdog/test/hotdog/1181.png  
  inflating: hotdog/test/hotdog/1354.png  
  inflating: hotdog/test/hotdog/1105.png  
 extracting: hotdog/test/hotdog/1144.png  
  inflating: hotdog/test/hotdog/1252.png  
  inflating: hotdog/test/hotdog/1249.png  
 extracting: hotdog/test/hotdog/1035.png  
 extracting: hotdog/test/hotdog/1365.png  
 extracting: hotdog/test/hotdog/1347.png  
  inflating: hotdog/test/hotdog/1005.png  
 extracting: hotdog/test/hotdog/1361.png  
  inflating: hotdog/test/hotdog/1038.png  
  inflating: hotdog/test/hotdog/1357.png  
  inflating: hotdog/test/hotdog/1070.png  
 extracting: hotdog/test/hotdog/1399.png  
 extracting: hotdog/test/hotdog/1113.png  
  inflating: hotdog/test/hotdog/1167.png  
  inflating: hotdog/test/hotdog/1112.png  
  inflating: hotdog/test/hotdog/1384.png  
  inflating: hotdog/test/hotdog/1213.png  
 extracting: hotdog/test/hotdog/1342.png  
  inflating: hotdog/test/hotdog/1362.png  
 extracting: hotdog/test/hotdog/1085.png  
  inflating: hotdog/test/hotdog/1131.png  
  inflating: hotdog/test/hotdog/1027.png  
  inflating: hotdog/test/hotdog/1002.png  
  inflating: hotdog/test/hotdog/1254.png  
  inflating: hotdog/test/hotdog/1291.png  
  inflating: hotdog/test/hotdog/1259.png  
  inflating: hotdog/test/hotdog/1121.png  
  inflating: hotdog/test/hotdog/1154.png  
  inflating: hotdog/test/hotdog/1279.png  
  inflating: hotdog/test/hotdog/1044.png  
  inflating: hotdog/test/hotdog/1314.png  
  inflating: hotdog/test/hotdog/1087.png  
  inflating: hotdog/test/hotdog/1311.png  
  inflating: hotdog/test/hotdog/1095.png  
  inflating: hotdog/test/hotdog/1056.png  
  inflating: hotdog/test/hotdog/1289.png  
  inflating: hotdog/test/hotdog/1351.png  
  inflating: hotdog/test/hotdog/1355.png  
  inflating: hotdog/test/hotdog/1352.png  
  inflating: hotdog/test/hotdog/1046.png  
  inflating: hotdog/test/hotdog/1052.png  
 extracting: hotdog/test/hotdog/1043.png  
  inflating: hotdog/test/hotdog/1356.png  
  inflating: hotdog/test/hotdog/1146.png  
  inflating: hotdog/test/hotdog/1283.png  
  inflating: hotdog/test/hotdog/1127.png  
  inflating: hotdog/test/hotdog/1107.png  
  inflating: hotdog/test/hotdog/1248.png  
  inflating: hotdog/test/hotdog/1376.png  
  inflating: hotdog/test/hotdog/1264.png  
  inflating: hotdog/test/hotdog/1394.png  
  inflating: hotdog/test/hotdog/1278.png  
 extracting: hotdog/test/hotdog/1120.png  
 extracting: hotdog/test/hotdog/1226.png  
  inflating: hotdog/test/hotdog/1323.png  
 extracting: hotdog/test/hotdog/1076.png  
 extracting: hotdog/test/hotdog/1083.png  
 extracting: hotdog/test/hotdog/1218.png  
  inflating: hotdog/test/hotdog/1363.png  
  inflating: hotdog/test/hotdog/1092.png  
  inflating: hotdog/test/hotdog/1014.png  
  inflating: hotdog/test/hotdog/1320.png  
  inflating: hotdog/test/hotdog/1074.png  
  inflating: hotdog/test/hotdog/1306.png  
 extracting: hotdog/test/hotdog/1081.png  
  inflating: hotdog/test/hotdog/1212.png  
  inflating: hotdog/test/hotdog/1251.png  
  inflating: hotdog/test/hotdog/1348.png  
  inflating: hotdog/test/hotdog/1166.png  
  inflating: hotdog/test/hotdog/1262.png  
  inflating: hotdog/test/hotdog/1300.png  
  inflating: hotdog/test/hotdog/1263.png  
 extracting: hotdog/test/hotdog/1360.png  
  inflating: hotdog/test/hotdog/1136.png  
  inflating: hotdog/test/hotdog/1164.png  
 extracting: hotdog/test/hotdog/1042.png  
 extracting: hotdog/test/hotdog/1340.png  
 extracting: hotdog/test/hotdog/1007.png  
  inflating: hotdog/test/hotdog/1302.png  
  inflating: hotdog/test/hotdog/1165.png  
  inflating: hotdog/test/hotdog/1031.png  
  inflating: hotdog/test/hotdog/1059.png  
 extracting: hotdog/test/hotdog/1137.png  
  inflating: hotdog/test/hotdog/1337.png  
  inflating: hotdog/test/hotdog/1225.png  
  inflating: hotdog/test/hotdog/1096.png  
  inflating: hotdog/test/hotdog/1308.png  
  inflating: hotdog/test/hotdog/1214.png  
  inflating: hotdog/test/hotdog/1037.png  
  inflating: hotdog/test/hotdog/1386.png  
  inflating: hotdog/test/hotdog/1250.png  
  inflating: hotdog/test/hotdog/1050.png  
 extracting: hotdog/test/hotdog/1318.png  
  inflating: hotdog/test/hotdog/1322.png  
  inflating: hotdog/test/hotdog/1020.png  
  inflating: hotdog/test/hotdog/1325.png  
  inflating: hotdog/test/hotdog/1238.png  
  inflating: hotdog/test/hotdog/1364.png  
 extracting: hotdog/test/hotdog/1098.png  
  inflating: hotdog/test/hotdog/1298.png  
  inflating: hotdog/test/hotdog/1296.png  
  inflating: hotdog/test/hotdog/1153.png  
  inflating: hotdog/test/hotdog/1025.png  
  inflating: hotdog/test/hotdog/1294.png  
  inflating: hotdog/test/hotdog/1117.png  
 extracting: hotdog/test/hotdog/1062.png  
  inflating: hotdog/test/hotdog/1017.png  
  inflating: hotdog/test/hotdog/1276.png  
  inflating: hotdog/test/hotdog/1011.png  
  inflating: hotdog/test/hotdog/1273.png  
 extracting: hotdog/test/hotdog/1317.png  
  inflating: hotdog/test/hotdog/1122.png  
 extracting: hotdog/test/hotdog/1346.png  
  inflating: hotdog/test/hotdog/1134.png  
  inflating: hotdog/test/hotdog/1115.png  
  inflating: hotdog/test/hotdog/1245.png  
  inflating: hotdog/test/hotdog/1270.png  
 extracting: hotdog/test/hotdog/1084.png  
  inflating: hotdog/test/hotdog/1390.png  
  inflating: hotdog/test/hotdog/1269.png  
  inflating: hotdog/test/hotdog/1330.png  
  inflating: hotdog/test/hotdog/1189.png  
 extracting: hotdog/test/hotdog/1022.png  
  inflating: hotdog/test/hotdog/1173.png  
 extracting: hotdog/test/hotdog/1288.png  
  inflating: hotdog/test/hotdog/1239.png  
  inflating: hotdog/test/hotdog/1256.png  
 extracting: hotdog/test/hotdog/1343.png  
  inflating: hotdog/test/hotdog/1193.png  
  inflating: hotdog/test/hotdog/1103.png  
  inflating: hotdog/test/hotdog/1333.png  
  inflating: hotdog/test/hotdog/1204.png  
  inflating: hotdog/test/hotdog/1194.png  
  inflating: hotdog/test/hotdog/1008.png  
  inflating: hotdog/test/hotdog/1215.png  
  inflating: hotdog/test/hotdog/1295.png  
  inflating: hotdog/test/hotdog/1150.png  
  inflating: hotdog/test/hotdog/1242.png  
  inflating: hotdog/test/hotdog/1210.png  
 extracting: hotdog/test/hotdog/1396.png  
  inflating: hotdog/test/hotdog/1055.png  
 extracting: hotdog/test/hotdog/1086.png  
  inflating: hotdog/test/hotdog/1258.png  
  inflating: hotdog/test/hotdog/1145.png  
  inflating: hotdog/test/hotdog/1338.png  
  inflating: hotdog/test/hotdog/1202.png  
  inflating: hotdog/test/hotdog/1353.png  
  inflating: hotdog/test/hotdog/1290.png  
  inflating: hotdog/test/hotdog/1132.png  
 extracting: hotdog/test/hotdog/1235.png  
  inflating: hotdog/test/hotdog/1039.png  
  inflating: hotdog/test/hotdog/1266.png  
  inflating: hotdog/test/hotdog/1023.png  
  inflating: hotdog/test/hotdog/1123.png  
  inflating: hotdog/test/hotdog/1163.png  
  inflating: hotdog/test/hotdog/1111.png  
 extracting: hotdog/test/hotdog/1057.png  
 extracting: hotdog/test/hotdog/1369.png  
  inflating: hotdog/test/hotdog/1331.png  
 extracting: hotdog/test/hotdog/1366.png  
  inflating: hotdog/test/hotdog/1237.png  
 extracting: hotdog/test/hotdog/1307.png  
  inflating: hotdog/test/hotdog/1313.png  
  inflating: hotdog/test/hotdog/1312.png  
  inflating: hotdog/test/hotdog/1126.png  
  inflating: hotdog/test/hotdog/1161.png  
  inflating: hotdog/test/hotdog/1003.png  
  inflating: hotdog/test/hotdog/1018.png  
  inflating: hotdog/test/hotdog/1280.png  
  inflating: hotdog/test/hotdog/1158.png  
  inflating: hotdog/test/hotdog/1128.png  
  inflating: hotdog/test/hotdog/1359.png  
  inflating: hotdog/test/hotdog/1341.png  
  inflating: hotdog/test/hotdog/1375.png  
  inflating: hotdog/test/hotdog/1149.png  
  inflating: hotdog/test/hotdog/1241.png  
  inflating: hotdog/test/hotdog/1094.png  
  inflating: hotdog/test/hotdog/1129.png  
  inflating: hotdog/test/hotdog/1332.png  
 extracting: hotdog/test/hotdog/1196.png  
  inflating: hotdog/test/hotdog/1004.png  
  inflating: hotdog/test/hotdog/1316.png  
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Kiedy korzystamy z sieci pretrenowanej na zbiorze ImageNet, zgodnie z dokumentacją trzeba dokonać standaryzacji naszych obrazów, odejmując średnią i dzieląc przez odchylenie standardowe każdego kanału ze zbioru ImageNet.

All pre-trained models expect input images normalized in the same way, i.e. mini-batches of 3-channel RGB images of shape (3 x H x W), where H and W are
expected to be at least 224. The images have to be loaded in to a range of [0, 1] and then normalized using mean = [0.485, 0.456, 0.406] and std = [0.229,
0.224, 0.225]. You can use the following transform to normalize:

normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406],
                                 std=[0.229, 0.224, 0.225])

In [59]:
torch.manual_seed(17)

normalize = transforms.Normalize(
    mean=[0.485, 0.456, 0.406],
    std=[0.229, 0.224, 0.225]
)

train_augs = torchvision.transforms.Compose(
    [
        torchvision.transforms.RandomResizedCrop(224),
        torchvision.transforms.RandomHorizontalFlip(),
        torchvision.transforms.ToTensor(),
        normalize,
    ]
)

test_augs = torchvision.transforms.Compose(
    [
        torchvision.transforms.Resize(256),
        torchvision.transforms.CenterCrop(224),
        torchvision.transforms.ToTensor(),
        normalize,
    ]
)
In [60]:
pretrained_net = torchvision.models.resnet18(weights=torchvision.models.ResNet18_Weights.IMAGENET1K_V1)
Downloading: 
100%|██████████| 44.7M/44.7M [00:01<00:00, 25.1MB/s]
In [61]:
pretrained_net.fc
Out[61]:
Linear(in_features=512, out_features=1000, bias=True)

Zadanie 5 (1 punkt)

Dodaj warstwę liniową do naszej fine-fune'owanej sieci oraz zainicjuj ją losowymi wartościami.

In [69]:
finetuned_net = pretrained_net
finetuned_net.fc = nn.Linear(in_features=512, out_features=2)
In [63]:
import time
import copy


def train_model(
    model, dataloaders, criterion, optimizer, num_epochs=25
):
    since = time.time()

    val_acc_history = []

    best_model_wts = copy.deepcopy(model.state_dict())
    best_acc = 0.0

    for epoch in range(1, num_epochs + 1):
        print("Epoch {}/{}".format(epoch, num_epochs))
        print("-" * 10)

        # Each epoch has a training and validation phase
        for phase in ["train", "val"]:
            if phase == "train":
                model.train()  # Set model to training mode
            else:
                model.eval()  # Set model to evaluate mode

            running_loss = 0.0
            running_corrects = 0

            # Iterate over data.
            for inputs, labels in dataloaders[phase]:
                inputs = inputs.to(device)
                labels = labels.to(device)

                # zero the parameter gradients
                optimizer.zero_grad()

                # forward
                # track history if only in train
                with torch.set_grad_enabled(phase == "train"):
                    # Get model outputs and calculate loss
                    
                    outputs = model(inputs)
                    loss = criterion(outputs, labels)
                    _, preds = torch.max(outputs, 1)

                    # backward + optimize only if in training phase
                    if phase == "train":
                        loss.backward()
                        optimizer.step()

                # statistics
                running_loss += loss.item() * inputs.size(0)
                running_corrects += torch.sum(preds == labels.data)

            epoch_loss = running_loss / len(dataloaders[phase].dataset)
            epoch_acc = running_corrects.float() / len(dataloaders[phase].dataset)

            print("{} Loss: {:.4f} Acc: {:.4f}".format(phase, epoch_loss, epoch_acc))

            # deep copy the model
            if phase == "val" and epoch_acc > best_acc:
                best_acc = epoch_acc
                best_model_wts = copy.deepcopy(model.state_dict())
            if phase == "val":
                val_acc_history.append(epoch_acc)

        print()

    time_elapsed = time.time() - since
    print(
        "Training complete in {:.0f}m {:.0f}s".format(
            time_elapsed // 60, time_elapsed % 60
        )
    )
    print("Best val Acc: {:4f}".format(best_acc))

    # load best model weights
    model.load_state_dict(best_model_wts)
    return model, val_acc_history
In [64]:
import os

data_dir = "hotdog"
batch_size = 32

model_ft = finetuned_net.to(device)
train_iter = torch.utils.data.DataLoader(
    torchvision.datasets.ImageFolder(
        os.path.join(data_dir, "train"), transform=train_augs
    ),
    batch_size=batch_size,
    shuffle=True,
)
test_iter = torch.utils.data.DataLoader(
    torchvision.datasets.ImageFolder(
        os.path.join(data_dir, "test"), transform=test_augs
    ),
    shuffle=True,
    batch_size=batch_size,
)
loss = nn.CrossEntropyLoss(reduction="none")

Zadanie 6 (1 punkt)

Zmodyfikuj tak parametry sieci, aby learning rate dla ostatniej warstwy był 10 razy wyższy niż dla pozostałych.

Trzeba odpowiednio podać pierwszy parametr torch.optim.SGD tak, aby zawierał parametry normalne, oraz te z lr * 10. Paramety warstw niższych to takie, które mają nazwę inną niż fc.weight albo fc.bias - może się przydać metoda sieci named_parameters().

In [67]:
def train_fine_tuning(net, learning_rate, num_epochs=15):

    backbone_params = []
    head_params = []

    for name, param in net.named_parameters():
        if name in ('fc.bias', 'fc.weight'):
            backbone_params.append(param)
        else:
            head_params.append(param)

    trainer = torch.optim.SGD([
        {'params' : backbone_params, 'lr' : learning_rate},
        {'params' : head_params, 'lr' : learning_rate * 10},
    ])
    
    dataloaders_dict = {"train": train_iter, "val": test_iter}
    criterion = nn.CrossEntropyLoss()
    model_ft, hist = train_model(
        net, dataloaders_dict, criterion, trainer, num_epochs=num_epochs
    )
    return model_ft, hist
In [71]:
model_ft, hist = train_fine_tuning(model_ft, learning_rate=5e-5)
Epoch 1/15
----------
train Loss: 0.6333 Acc: 0.6265
val Loss: 0.5871 Acc: 0.6662

Epoch 2/15
----------
train Loss: 0.5511 Acc: 0.7280
val Loss: 0.5085 Acc: 0.7600

Epoch 3/15
----------
train Loss: 0.4893 Acc: 0.7955
val Loss: 0.4626 Acc: 0.8200

Epoch 4/15
----------
train Loss: 0.4472 Acc: 0.8355
val Loss: 0.4211 Acc: 0.8575

Epoch 5/15
----------
train Loss: 0.4254 Acc: 0.8435
val Loss: 0.3916 Acc: 0.8725

Epoch 6/15
----------
train Loss: 0.3969 Acc: 0.8505
val Loss: 0.3672 Acc: 0.8850

Epoch 7/15
----------
train Loss: 0.3686 Acc: 0.8720
val Loss: 0.3445 Acc: 0.8950

Epoch 8/15
----------
train Loss: 0.3579 Acc: 0.8645
val Loss: 0.3265 Acc: 0.8963

Epoch 9/15
----------
train Loss: 0.3470 Acc: 0.8780
val Loss: 0.3114 Acc: 0.9013

Epoch 10/15
----------
train Loss: 0.3259 Acc: 0.8870
val Loss: 0.2992 Acc: 0.9075

Epoch 11/15
----------
train Loss: 0.3261 Acc: 0.8810
val Loss: 0.2872 Acc: 0.9100

Epoch 12/15
----------
train Loss: 0.2987 Acc: 0.8980
val Loss: 0.2735 Acc: 0.9150

Epoch 13/15
----------
train Loss: 0.3007 Acc: 0.8910
val Loss: 0.2698 Acc: 0.9112

Epoch 14/15
----------
train Loss: 0.2841 Acc: 0.9045
val Loss: 0.2600 Acc: 0.9175

Epoch 15/15
----------
train Loss: 0.2865 Acc: 0.8915
val Loss: 0.2516 Acc: 0.9125

Training complete in 56m 43s
Best val Acc: 0.917500

skomentuj wyniki:

  • Wraz z każdą kolejną epoką, możemy zauważyć spadek wartości funkcji straty na zbiorze walidacyjnym, przy jednoczesnym zwiększeniu dokładności (accuracy)
  • dzieje się tak głównie do 12 epoki, po niej możemy zauważyć lekkie fluktuację w otrzymanej dokladności na zbiorze walidacyjnym
  • Pomimo powyższych, wyniki wydają się być bardzo zadowalające

Przy wyświetlaniu predykcji sieci musimy wykonać operacje odwrotne niż te, które wykonaliśmy, przygotowując obrazy do treningu:

  • zamienić kolejność kanałów z (C, H, W) na (H, W, C)
  • zamienić obraz z tensora na tablicę Numpy'a
  • odwrócić normalizację (mnożymy przez odchylenie standardowe, dodajemy średnią) i upewnić się, że nie wychodzimy poza zakres [0, 1] (wystarczy proste przycięcie wartości)
In [72]:
def imshow(img, title=None):
    img = img.permute(1, 2, 0).numpy()
    means = np.array([0.485, 0.456, 0.406])
    stds = np.array([0.229, 0.224, 0.225])
    img = stds * img + means
    img = np.clip(img, 0, 1)

    plt.imshow(img)
    if title is not None:
        plt.title(title)
    
    plt.pause(0.001)
In [74]:
import matplotlib.pyplot as plt
plt.ion()  


def visualize_model(model, num_images=6):
    class_names = ["hotdog", "other"]
    model.eval()
    images_so_far = 0
    fig = plt.figure()
    with torch.no_grad():
        for i, (inputs, labels) in enumerate(test_iter):
            inputs = inputs.to(device)
            labels = labels.to(device)

            outputs = model(inputs)
            _, preds = torch.max(outputs, 1)

            for j in range(inputs.size()[0]):
                images_so_far += 1
                ax = plt.subplot(num_images // 2, 2, images_so_far)
                ax.axis('off')
                ax.set_title(f'predicted: {class_names[preds[j]]}')

                imshow(inputs.data[j].cpu())

                if images_so_far == num_images:
                    return
In [78]:
visualize_model(model_ft)
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Zadanie dla chętnych (3 punkty)¶

W zadaniach dotyczących klasyfikacji obrazu wykorzystywaliśmy prosty zbiór danych i sieć LeNet. Teraz zamień zbiór danych na bardziej skomplikowany, np. ten lub ten (lub inny o podobnym poziomie trudności) i zamiast prostej sieci LeNet użyj bardziej złożonej, np. AlexNet, ResNet, MobileNetV2.

In [ ]: